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Balasubramanian, ArunKumar. "Benchmarking of Vision-Based Prototyping and Testing Tools." Master's thesis, Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-229999.
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The demand for Advanced Driver Assistance System (ADAS) applications is increasing day by day and their development requires efficient prototyping and real time testing. ADTF (Automotive Data and Time Triggered Framework) is a software tool from Elektrobit which is used for Development, Validation and Visualization of Vision based applications, mainly for ADAS and Autonomous driving. With the help of ADTF tool, Image or Video data can be recorded and visualized and also the testing of data can be processed both on-line and off-line. The development of ADAS applications needs image and video processing and the algorithm has to be highly efficient and must satisfy Real-time requirements. The main objective of this research would be to integrate OpenCV library with ADTF cross platform. OpenCV libraries provide efficient image processing algorithms which can be used with ADTF for quick benchmarking and testing. An ADTF filter framework has been developed where the OpenCV algorithms can be directly used and the testing of the framework is carried out with .DAT and image files with a modular approach. CMake is also explained in this thesis to build the system with ease of use. The ADTF filters are developed in Microsoft Visual Studio 2010 in C++ and OpenMP API are used for Parallel programming approach.
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Hasnat, Md Abul. "Detection of circular bounding box in video streams." Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-206272.
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The production line of industries are getting more efficient and having very high throughput. Different kinds of machineries are being used to make the production safe, fast, precise and reliable. Robot arm is such a machine which helps the production line to be more efficient and productive. Nowadays, many manufacturing industries are using robot-arms to get a competitive edge in manufacturing and can be outfitted for multiple applications like welding, material handling, thermal spraying, painting, drilling and so on. They are widely used to increase product quality and production demand and over all, to ensure safer, faster and efficient production. It is very important to control and maintain these machines very accurately. As a simple mistake of robot arm can cause excessive destructions and bring financial losses to the industries, the robotarms must be very accurate when they are functioning in their production settings.
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Ruggeri, Eugenio. "Tracking di oggetti mediante la libreria opencv." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7864/.
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Varano, Pietro. "Elaborazioni di immagini con la libreria OpenCV." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amslaurea.unibo.it/810/.
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Kumar, Surinder. "Lane Detection based on Contrast Analysis." Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-206227.
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Computer vision and image processing systems are ubiquitous in automotive domain and manufacturing industry. Lane detection warning systems has been an elementary part of the modern automotive industry. Due to the recent progress in the computer vision and image processing methods, economical and flexible use of computer vision is now pervasive and computing with images is not just for the realm of the science, but also for the arts and social science and even for hobbyists. Image processing is a key technology in automotive industry, even now there is hardly a single manufacturing process that is thinkable without imaging. The applications of image processing and computer vision methods in embedded systems platform, is an ongoing research area since many years. OpenCV, an open-source computer vision library containing optimized algorithms and methods for designing and implementing applications based on video and image processing techniques. These method are organized in the form of modules for specific field including, user-graphic interface, machine learning, feature extraction etc [43]. Vision-based automotive application systems become an important mechanism for lane detection and warning systems to alert a driver about the road in localization of the vehicle [1]. In automotive electronic market, for lane detection problem, vision-based approaches has been designed and developed using different electronic hardware and software components including wireless sensor, camera module, Field-Programmable Gate Array (FPGA) based systems, GPU and digital signal processors (DSP) [13]. The software module consists on the top of real-time operating systems and hardware description programming language including Verilog, or VHDL. One of the most time critical task of vision based systems is to test system applications in real physical environment with wide variety of driving scenarios and validating the whole systems as per the automotive industry standards. For validating and testing the advanced driver assistance systems, there are some commercial tools available including Assist ADTF from Elektrobit, EB company [43]. In addition to the design and strict real-time requirements for advanced driver assistance systems applications based on electronic components and embedded platform, the complexity and characteristics of the implemented algorithms are two parameters that need to be taken into consideration choosing hardware and software component [13]. The development of vision-based automotive application, based on alone electronic and micro-controller is not a feasible solution approach [35] [13] and GPU based solution are attractive but has many other issues including power consumption. In this thesis project, image and video processing module is used from OpenCV library for road lane detection problems. In proposed lane detection methods, low-level image processing algorithms and methods are used to extract relevant information for lane detection problem by applying contrast analysis at pixel level intensity values. Furthermore, the work at hand presents different approaches for solving relevant partial problems in the domain of lane detection. The aim of the work is to apply contrast analysis based on low-level image processing methods to extract relevant lane model information from the grid of intensity values of pixel elements available in image frame. The approaches presented in this project work are based on contrast analysis of binary mask image frame extracted after applying range threshold. A set of points, available in an image frame, based lane feature models are used for detecting lanes on color image frame captured from video. For the performance measurement and evaluation, the proposed methods are tested on different systems setup, including Linux, Microsoft Windows, CodeBlocks, Visual Studio 2012 and Linux based Rasbian-Jessie operating systems running on Intel i3, AMD A8 APU, and embedded systems based (Raspberry Pi 2 Model B) ARM v7 processor respectively.
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Lotankar, Akshay Naresh. "Development of a smart-phone based augmented reality view application for driver assistance systems." Master's thesis, Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-229312.
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The goal of this thesis is to develop a smartphone application for augmented reality view; it is an initial attempt to realize a driver assistance functionality using just a smartphone and an external lens. Initially it depicts a brief analysis about the most feasible development technologies for mobile application development, selecting a proper lens and positioning of the smartphone in the car. Later, it discusses the strategies for real-time object detection using OpenCV; the video frames are processed using the strategies to find patterns in the videos. Different techniques like Hough-line transform, watershed, contour detection, color segmentation, color thresholding and HAAR cascades are implemented and compared in terms of real time detection of the desired objects. Then a unified algorithm is implemented for the given scenario which overcomes the challenges faced during the conceptualization phase. Finally, the results are depicted with the snapshots of the real time detection done from the smartphone and then evaluated against the vision of the application and the achieved tasks. This thesis is concluded by stating the prospects of this mobile application in the future.
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Maddison, John. "Automatisk validering av skärmgrafik med OpenCV och Tesseract." Thesis, Linköpings universitet, Programvara och system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151912.
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I dagens flygplan finns det mycket information som på ett snabbt och pålitligt sätt behöver förmedlas till piloten via instrument på flera skärmar i cockpit. Att verifiera att skärmarna visar korrekt data för olika indata är ett tidskrävande och monotont arbete. Därför undersöker Saab möjligheten att automatisera delar av arbetet. Examensarbetet undersöker genom praktiskt implementation ifall det är möjligt att automatisera bildanalysen med hjälp av programmen OpenCV och Tesseract. Resultatet visade att det går att enkelt konstruera tester för att automatiskt identifiera oönskade förändringar i den implementerade instrumentingen.
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Phothithiraphong, Thanaset. "Automated Enrichment of Global World View Information based on Car2X." Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-204974.
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The purpose of this thesis is to develop the architecture to use the Car2X for observation the local traffic sign and displays it on the OpenStreetMap to provide more information of the road side to the driver. The proposed architecture of this thesis is to convert the traffic sign into the barcode and to be scanned by the barcode scanner and then wirelessly transfers the data to the web server to store the data and displays the traffic sign on the OpenStreetMap in the web browser. It uses two Raspberry Pi boards with CAN-Bus shields for transmitting the data on the CAN-Bus system in the car, a barcode scanner to scan the barcode, a GPS module to get its location, and a WiFi dongle to wirelessly send the data. The thesis also includes the camera to detect the traffic light using OpenCV and sends the GO or STOP command to the car. The results provide the OpenStreetMap with the traffic sign which helps the driver to realize the traffic sign on the road of the desired destination. However, the accuracy of GPS is not satisfied as well as the distance of the barcode scanning, therefore, this thesis suggests that includes the gps position in the barcode and uses the camera to detect the barcode for the improvement in the future.
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Tonelli, Alfredo. "Image Processing e Computer Vision con Python e OpenCV." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20390/.
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Studio di uno degli ecosistemi software oggi maggiormente utilizzati per Image Processing e Computer Vision.
Lo studio affrontato parte dalle discipline di Image Processing e Computer Vision, passando per le principali soluzioni software adottate, tra le quali spiccano il linguaggio di programmazione ad alto livello Python e la libreria di Computer Vision OpenCV, per terminare con esempi pratici di base utili per capire il funzionamento delle tecnologie illustrate.
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Семенов, О. В. "Визначення розмірів об’єктів на зображенні за допомогою бібліотеки Opencv." Thesis, Чернігів, 2021. http://ir.stu.cn.ua/123456789/23095.
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Семенов, О. В. Визначення розмірів об’єктів на зображенні за допомогою бібліотеки Opencv : випускна кваліфікаційна робота : 123 "Кoмп’ютepнa iнжeнepiя" / О. В. Семенов ; керівник роботи В. В. Казимир ; НУ "Чернігівська політехніка", кафедра iнфopмaцiйниx тa кoмп’ютepниx cиcтeм. – Чернігів, 2021. – 77 с.Об’єктом дослідження даної роботи є процес розпізнавання об’єктів на зображенні з використанням методів комп’ютерної інженерії. Метою роботи є розробка проекту по знаходженню розмірів одягу на зображенні з використанням бібліотеки OpenCV. В першому розділі було проведено теоретичні дослідження існуючих бібліотек і їх порівняння на основі особливостей практичного застосування при розпізнаванні об’єктів на зображенні. В другому розділі був проведений вибір технічних засобів для побудови системи. В третьому розділі проведено визначення розмірів на зображенні. Об’єктом є процес розпізнавання об’єктів на зображенні з використанням методів комп’ютерної інженерії. Предметом дослідження виступають теоретичні основи та прикладні підходи до реалізації процесу розпізнавання об’єктів на зображенні з використанням методів комп’ютерної інженерії.
The object of research of this work is the process of recognizing objects in the image using computer engineering methods. The purpose of the work is to develop an application to find the parameters of the garment on the image using the OpenCV library. In the first section were reviewed the theoretical studies of existing libraries and carried out their comparison on the basis of features of practical application in recognizing objects in the image. In the second section, a selection of technical means for building the system was made. In the third section was the process of determining the parameters of the garment in the image. The object is the process of recognizing objects in the image using computer engineering methods. The subject of the study is the theoretical foundations and applied approaches for implementation recognition systems for measuring the parameters in the image using computer engineering methods.
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Marchal, Jakob, and Mathias Andreasen Andreasen. "Autopositionering för röntgensystem." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-42742.
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Abstrakt Röntgen är ett område där man ställer frågan om processen skulle kunna automatiseras för att göra den enklare för sjuksköterskor. På så sätt ökar antalet patienter som kan röntgas eftersom det skulle gå snabbare. Med hjälp av datorseende och en servostyrd röntgenkamera kan man förverkliga delar av dessa drömmar genom att låta röntgenkameran själv justera sig efter en patient och även flyttas till en vald kroppsdel. Här undersöks och testas open-source biblioteket OpenCV. En prototyp på ett automatiskt system tas fram med syftet att testa OpenCVs funktionalitet och besvara ett antal frågor: Hur kan röntgen automatiseras genom användning av open-source programvarubibliotek med inriktning på bildbehandling? Vilka för – och nackdelar kan användandet av ett datorseendebibliotek vara? Kan man med dagens teknik utveckla en automatisk lösning som kan göras till en kommersiell produkt?
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Martinsson, Jonas. "Examine vision technology for small object recognition in an industrial robotics application." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-28218.
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This thesis explains the development of a computer vision system able to find and orient relatively small objects. The motivations is exchanging a monotonous work done by hand and replace it with an automation system with help of an ABB IRB 140 industrial robot. The vision system runs on a standard PC and is developed using the OpenCV environment, originally made by Intel in Russia. The algorithms of the system is written in C++ and the user interface in C++/CLI. With a derived test case, multiple vision algorithms is tested and evaluated for this kind of application. The result shows that SIFT/SURF works poorly with multiple instances of the search object and HAAR classifiers produces many false positives. Template matching with image moment calculation gave a satisfying result regarding multiple object in the scene and produces no false positives. Drawbacks of the selected algorithm developed where sensibility to light invariance and lack of performance in a skewed scene. The report also contains suggestions on how to precede with further improvements or research.
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Udovenko, Nikita. "3D geometrijos atstatymas panaudojant Kinect jutiklį." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2012. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120723_110949-72095.
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Šiame darbe yra tiriamos atrankiojo aplinkos 3D geometrijos atstatymo galimybės panaudojant Kinect jutiklio kombinuotą vaizdo-gylio kamerą: pateikiamas matematinis atstatymo modelis, jo parametrizavimui reikalingi koeficientai, apibūdinama tikėtinų paklaidų apimtis, siūloma aktualių scenos duomenų išskyrimo iš scenos procedūra, tiriamas gaunamo modelio triukšmas ir jo pašalinimo galimybės ir metodai. Atstatyta geometrija yra pateikiama metrinėje matų sistemoje, ir kiekvienas 3D scenos taškas papildomai saugo savo spalvinę informaciją. Praktinėje dalyje pateikiama sukurta taikomoji programa yra įgyvendinta naudojant C++ ir OpenCV matematines programavimo bibliotekas. Ji atlieka 3D geometrijos atstatymą pagal pateiktą teorinį modelį, išskiria aktualius scenos duomenis, pašalina triukšmą ir gali išsaugoti gautus duomenis į 3D modeliavimo programoms suprantamą PLY formato bylą. Darbą sudaro: įvadas, 3 skyriai, išvados ir literatūros sąrašas. Darbo apimtis – 61 p. teksto be priedų, 43 paveikslai, 4 lentelės, 22 bibliografiniai šaltiniai.The purpose of this thesis is to investigate the possibilities of selective 3D geometry reconstruction using Kinect combined image-depth camera: a mathematical reconstruction model is provided, as well as coefficients to parametrize it and estimates on expected precision; a procedure on filtering out the background from depth image is proposed, depth image noise and possibilities for its removal are studied. Resulting reconstructed geometry is provided using metric system of measurement, and each 3D point also retains it's color data. Resulting application is implemented in C++ programming language and uses OpenCV programming library. It implements 3D geometry reconstruction as described in theory section, removes background from depth image, as well as noise, and is able to save the resulting 3D geometry to a 3D modeling applications readable file format. Structure: introduction, 3 chapters, conclusions, references. Thesis consists of – 61 p. of text, 43 figures, 4 tables, 22 bibliographical entries.
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Tamošiūnas, Darius. "Vaizdo atpažinimas dirbtiniais neuroniniais tinklais." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140724_105651-16686.
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Darbe aprašoma tyrimas, kurio metu buvo sukurta programa, naudojantis OpenCV ir DNT klaidos skleidimo atgal algoritmu, gebanti aptikti ir bandanti klasifikuoti veidus. Darbo eigoje: • Įsigilinta į OpenCV funkcijų biblioteką; • Išanalizuota DNT teorinė medžiaga; • Sukurta programinė įranga, kuri, naudojantis „webcam“, geba aptikti ir bando klasifikuoti veidus; • Atliktas eksperimentinis tyrimas; • Nustatyti programos trūkumai; • Pateikti kiti sprendimo būdai; Realizuota programinė įranga gali būti naudojama edukaciniais tikslais.The work describes an experiment,in which progress was created a software,by using OpenCV and ANN error back propagation algorithm capable of detecting and attempting to classify the faces. Workflow: • Delved deeply into the OpenCV library functions; • Analyzed the theoretical material of ANN • Developed the software, which, using webcam, is capable of detecting and trying to classify the faces; • Made an experimental study; • Determined the weaknesses of the program; • The other methods; created software can be used for educational purposes.
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Kovář, Jan. "Detekce rychlosti přibližování automobilu na základě zpracování obrazu kamery." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-374602.
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The thesis deals with digital image processing, from the initial acquisition of digital picture frames, subsequent processing segmentation and algorithms to detect visual shapes on the scene. Image processing is a very broad topic, so here are analyzed for more understanding of the fundamental principles of perception and processing of video signals, image representation, his starting shooting through filters governing digital image processing methods to detect the objects in an image. It is also demonstrated by the size dependence of the object in the image on the distance from the camera, whereby we can determine the speed of approaching or moving away from the object. We will show you the specific determination of the distance we need to know the actual result size of the object. This is because the ratio between the size of the object depending on the distance is the same for each object. Finally, this work presents the resulting image frames for implementation using OpenCV library.
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Zetterlund, Samuel. "Blind swimmer detection and notification utilizing OpenCV on the Android platform." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-25084.
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For a blind swimmer to be able to exercise in a swimming pool today, human assistance is required to notifying the swimmer in due time when and if she is too close to the edge. The purpose of this thesis was to see whether or not it is possible to replace and even improve the human intervention using a warning system built around a tablet mounted next to the pool edge. A secondary goal was to evaluate how suitable a tablet pc is for robotic applications. The system proposed utilizes a tablet’s built-in frontal facing camera, OpenCV as vision library, FM modules for the wireless warning system and is intended for the Android environment. Videos of the real scenario have been analyzed on a computer using OpenCV and a detection algorithm searching for the swimmer’s red swimming cap has been developed. Next, the algorithm was implemented on an Android tablet. The result obtained shows that it is perfectly possible to use a cheap tablet to accurately detect and notify the blind swimmer in due time when she is too close to the edge. If calibrated thoroughly, the likelihood of a missed detection is actually lower with this system as compared to human intervention, as humans can only warn the swimmer when she is above the water.
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Lokkin, Caj, and Sebastian Bragd. "Öppen källkodslösning för datorseende : Skapande av testmiljö och utvärdering av OpenCV." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84511.
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Datorseende är ett område inom datavetenskap som har utvecklats i många år och funktionaliteten är mer tillgängligt nu än någonsin. Det kan bland annat användas för beröringfri mätning så som att hitta, verifiera och identifiera defekter för objekt. Frågan är om det går att utforma en öppen källkodslösning för datorseende som ger motsvarande prestanda som tillgängliga kommersiella. Med andra ord, kan ett företag som använder ett kommersiellt program med stängd källkod istället använda ett gratis öppet källkodsblibotek och få motsvarande resultat? I denna rapport beskriver vi designen av en prototyp som använder det öppna källkodsbiblioteket för datorseende, OpenCV. I syfte att utvärdera vår prototyp låter vi den identifiera block i ett torn på en bild i en serie testfall. Vi jämför resultaten från prototypen med de resultat som erhålls med en kommersiell lösning, skapad med programmet 'Vision Builder for Automated Inspection'. Resultat av det som testats visar att OpenCV tycks ha prestanda och funktionalitet som motsvarar den kommersiella lösningen men har begränsningar. Då OpenCV är fokus är på programmatisk utveckling av datorseenden lösningar är resultatet av lösningar som skapas beroende på användarens kompetens inom programmering och programmdesign. Utifrån de tester som genomfördes anser vi att OpenCV kan ersätta ett licensierat kommersiellt program men licensenkostnaderna kan komma att ersättas av andra utvecklingskostnader.Computer vision is a subject in computer science that have evolved over many years and the functionality is more accessible then ever. Among other things, it can be used for non-contact measurement to locate, verify, and detect defects of objects. The question is if it is possible to create an open source solution for computer vision equivalent to a closed source solution. In other words, can a company using a closed source commercial program instead use a free open source code library and produce equivalent results? In this report we describe the design of a prototype that uses the open source library for computer vision, OpenCV. In order to evaluate our prototype, we let it identify block in a tower on image in a series of test cases. We compare the results from the prototype with the results obtained with a commercial solution, created with the program ''Vision Builder for Automated Inspection''. Results from the cases tested show that OpenCV seems to have performance and functionality equivalent to the commercial solution but has some limitations. As OpenCV's focus is on programmatic development of computer vision solutions, the result is dependent on the user's skills in programming and program design. Based on the tests that we have performed, we believe that OpenCV can replace a licensed commerical program, but the license cost may come to be replaced by other development costs.
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Blomgren, Staffan, and Marcus Hertz. "Facing the differences between Facebook and OpenCV : A facial detection comparison between Open Library Computer Vision and Facebook." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166281.
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Face detection is used in many different areas and with this thesis we aim to show the difference between Facebooks face detection soft-ware compared with an open source version from OpenCV. By using the simplest implementation of OpenCV we want to find out if it is viable for use in personal applications and be of help for others wanting to implement face detection. The dataset was meticulously checked to find the exact number of faces in each image so that the optimal result is given. The conclusion of this study is that Facebooks algorithm is better trained and thus has better results, however OpenCV is still a viable choice for your own applications.
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Reinius, Staffan. "Object recognition using the OpenCV Haar cascade-classifier on the iOS platform." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-193282.
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Augmented reality (AR), the compiling of layered computer-generated information to real-time stream data, has recently become a buzzword in the mobile application communities, as real-time vision computing has become more and more feasible. Hardware advances have allowed numerous such utility and game applications to be deployed to mobile devices. This report presents a high-level implementation of live object recognition of automobile interiors, using Open Source Computer Vision Library (OpenCV) on the iOS platform. Two mobile devices where used for image processing: an iPhone 3GS and an iPhone 4. A handful of key-feature matching technics and one supervised learning classification approach were considered for this implementation. Speeded Up Robust Features (SURF) detection (a key-feature matching technique) and Haar classification (supervised learning approach) were implemented, and Haar classification was used in the final AR prototype. Although the object classifiers are not yet to satisfaction in terms of accuracy, a problem that could be overcome by more extensive training, the implementation performs sufficiently in terms of speed for the purpose of this AR prototype.
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Pini, Mattia. "Sviluppo di un Prototipo di Video Sorveglianza Indoor con Tecnologie YOLO ed OpenCV." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18178/.
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In questa tesi viene effettuato uno studio sulla reale efficienza delle Reti Neurali Artificiali e più in particolare delle Convolutional Neural Network nel settore del riconoscimento immagini e della velocità con cui è possibile ottenere informazioni dettagliate da esse.
Viene presentato quindi un Prototipo di Video Sorveglianza per Ambienti Indoor che sfrutta queste tecnologie in maniera efficiente coniugando lo stato dell'arte per il riconoscimento degli oggetti con algoritmi noti per il riconoscimento facciale.
Con un attento studio si è dimostrato inoltre perchè la rete scelta è risultata ottimale per l'obiettivo della tesi, mostrandone peculiarità e prestazioni.
Vengono inoltre affrontate le problematiche che gli algoritmi di riconoscimento facciale classici possiedono, di come l'inclinazione di un volto possa portare a un non riconoscimento della figura dello stesso, e le soluzioni proposte.
Importante inoltre la scelta del dataset per il riconoscimento facciale, poichè una scelta errata potrebbe portare a falsi positivi.
Il risultato è un sistema che attraverso acquisizione immagini da videocamera e attraverso l'uso di reti neurali riesce a verificare se un determinato oggetto o una persona sono realmente presenti o meno all'interno di un ambiente.
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Johansson, Henrik. "Evaluating Vivado High-Level Synthesis on OpenCV Functions for the Zynq-7000 FPGA." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-29591.
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More complex and intricate Computer Vision algorithms combined with higher resolution image streams put bigger and bigger demands on processing power. CPU clock frequencies are now pushing the limits of possible speeds, and have instead started growing in number of cores. Most Computer Vision algorithms' performance respond well to parallel solutions. Dividing the algorithm over 4-8 CPU cores can give a good speed-up, but using chips with Programmable Logic (PL) such as FPGA's can give even more. An interesting recent addition to the FPGA family is a System on Chip (SoC) that combines a CPU and an FPGA in one chip, such as the Zynq-7000 series from Xilinx. This tight integration between the Programmable Logic and Processing System (PS) opens up for designs where C programs can use the programmable logic to accelerate selected parts of the algorithm, while still behaving like a C program. On that subject, Xilinx has introduced a new High-Level Synthesis Tool (HLST) called Vivado HLS, which has the power to accelerate C code by synthesizing it to Hardware Description Language (HDL) code. This potentially bridges two otherwise very separate worlds; the ever popular OpenCV library and FPGAs. This thesis will focus on evaluating Vivado HLS from Xilinx primarily with image processing in mind for potential use on GIMME-2; a system with a Zynq-7020 SoC and two high resolution image sensors, tailored for stereo vision.
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Oliveira, J?nior Francisco Alves de. "IDENTIFICA??O E CLASSIFICA??O DE SINALIZA??O HORIZONTAL EM AUTOVIAS UTILIZANDO OPENCV." reponame:Repositório Institucional do IFPB, 2016. http://repositorio.ifpb.edu.br/jspui/handle/177683/266.
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Acidentes de tr?nsito podem ser fatais, causando a morte ou invalidez de motoristas e pedestres. Desta forma, muitos pesquisadores est?o desenvolvendo meios para deixar os ve?culos mais seguros, atrav?s do uso de sistemas de apoio ? condu??o que auxiliem os motoristas nas mais diversas situa??es no tr?nsito. O objetivo deste trabalho ? propor um sistema para detec??o e classifica??o de linhas de sinaliza??o horizontais em autovias. Sistemas deste tipo podem ajudar a diminuir a quantidade de acidentes de tr?nsito, auxiliando o condutor do ve?culo a permanecer em sua faixa e realizar ultrapassagens apenas em locais permitidos. As imagens das autovias, capturadas por uma c?mera fixada ao para-brisa no interior do ve?culo, s?o analisadas quadro a quadro em tempo real. O sistema proposto foi desenvolvido na linguagem de programa??o C++, utilizando a biblioteca OpenCV, de c?digo aberto, amplamente empregada em vis?o computacional. Dentre outras t?cnicas, utilizou-se o detector de bordas de Canny e a Transformada Probabil?stica de Hough para identifica??o de segmentos de reta. Adicionalmente, foram desenvolvidos m?todos geom?tricos para otimiza??o e elimina??o de segmentos desnecess?rios e um algoritmo para estima??o do ponto de fuga, o qual auxilia na identifica??o dos segmentos mais relevantes para o sistema. Foram realizados sete experimentos apresentando diferentes n?veis de dificuldade. Acur?cias na faixa de valores de 86,58% a 100% foram alcan?adas. Em m?dia, os experimentos obtiveram uma acur?cia de 94,56% na classifica??o dos diferentes tipos de sinaliza??es horizontais.
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Hagelin, Rickard, and Thomas Andersson. "Sammanfogning av videosekvenser från flygburna kameror." Thesis, Linköpings universitet, Informationskodning, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97029.
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The usage of Unmanned Aerial Vehicles (UAV) for several applications has in-creased during the past years. One of the possible applications are aerial imagecapturing for detection and surveillance purposes. In order to make the captur-ing process more efficient, multiple, cameraequipped UAV:s could fly in a for-mation and as a result cover a larger area. To be able to receive several imagesequences and stitch those together, resulting in a panoramavideo, a softwareapplication has been developed and tested for this purpose.All functionality are developed in the language C++ by using the software li-brary OpenCV. All implementations of different techniques and methods hasbeen done as generic as possible to be able to add functionality in the future.Common methods in computervision and object recognition such as SIFT, SURF and RANSAC have been tested.Användningen av UAV:er för olika tillämpningar har ökat under senare år. Ett avmöjliga användningsområden är flygfotografering och övervakning. För att gö-ra bildupptagningen mer effektiv kan flera UAV:er flyga i formation och på så viskunna fotografera ett avsevärt större område. För att kunna ta in flera bildsekven-ser och foga samman dessa till en panoramavideo, har ett program utvecklats ochtestats för denna uppgift.All funktionalitet för inläsning av bilder och video har utvecklats i C++ medprogrambiblioteket OpenCV. Implementeringen av dessa tekniker och metoderhar gjort så generiskt som möjligt för att det ska vara lättare att lägga till and-ra tekniker och utöka programmets funktioner. Olika tekniker som har testatsinkluderar: SIFT, SURF och RANSAC
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Matziaris, Spyridon. "Barcode Mapping in Warehouses." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-32385.
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Automation in warehouses has been improved in a very certain manner, combining sensors for perception of the environment and mapping of the warehouse. The most common characteristic, which makes the products and the pallet rack cells discriminative, are the barcodes placed on them. This means that the warehouse management system should successfully perceive all the necessary information of the detected barcodes, which also includes their position in the warehouse and build a barcode map of the environment. For this process a barcode reader is needed, with extended capabilities such as estimation of the 3-dimensional coordinates of the barcodes. The main idea of this research was the development of a system to be used in future work, placed on the roof of a forklift, which will be able to detect the barcodes and localize itself using an existing map of the warehouse and update new information in this map. However, the purpose of this project was the investigation of a suitable system for barcode mapping. The main challenge of this project was the development of a barcode reader, which fulfills all the referred capabilities and the comparison with a commercial reader in order to evaluate the performance of the system. In this project a barcode reader was developed using software libraries and a camera for industrial use. The performance of the system was compared with a commercial barcode reader. Moreover, an algorithm was implemented, for estimation of the position of each detected barcode, with reference to the position of the camera's lens. According to the results of all the investigations the performance of the developed system was quiet satisfying and promising. The comparison of the two systems proved that the commercial barcode reader had a better performance than the implemented system. However, it lacked the ability to provide the required information for mapping also the flexibility for integration with other systems. Overall, the developed system proved to be suitable for integration with a warehouse management system for barcode mapping of the environment.
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Johansson, Joakim. "Avståndsvarnare till Mobiltelefon." Thesis, Högskolan Väst, Institutionen för ekonomi och it, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-3480.
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This report describes a study, description and testing of parts to an application adapted to the operating system Android. The application is supposed to measure the distance to a car ahead. Apart from distance measurements the ability of the application to calculate its own speed with the help of GPS is tested. From these two parameters, speed, distance and some constants the theoretical stopping distance of the car will be calculated in order to warn the driver if the car is too close to the car ahead in relation to its own speed and stopping distance. Tests were conducted on the different applications that were programmed and the result showed that the camera technique in the mobile phone itself limits the maximum distance of the distance measurement application. The max distance the tests in this thesis revealed was approximately 5 meters. The measurement done to the GPS speed calculating application showed that the application was more accurate than the speedometer in the test car. The result of this thesis was that if all the parts were to be put together to a single application the maximum speed that it could be used with some functionality was 13,8 kilometers/hour assuming that the car ahead is at a standstill and the camera on the mobile phone is in a straight line from the license plate.Denna uppsats beskriver en studie, utveckling och testning av delar och teknik till en applikation anpassad till operativsystemet Android. Applikationen skall kunna mäta avståndet till framförvarande bil. Utöver avståndsmätning så testas applikationens förmåga att kalkylera sin egna hastighet med hjälp av GPS. Utifrån dessa två parametrar, hastighet och avstånd samt några konstanter skall den teoretiska stoppsträckan kunna räknas ut för att kunna varna om fordonet är för nära farmförvarande bil i förhållande till sin egna fart.. Tester utfördes på de olika applikationerna som programmerades och resultatet visade att tekniken i sig sätter stopp för att kunna mäta avståndet till nummerplåten på ett längre avstånd än ca 5m. Mätning av hastigheten var mer noggrann än hastighetsmätaren i bilen. Resultatet blev att om alla delar sattes ihop till en enda applikation så skulle den i bästa fall kunna användas i maximalt 13,8 km/h förutsatt att framförvarande bil är stillastående, och att kameran från telefonen är i en rak vinkel mot framförvarande nummerplåt.
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Hošek, Roman. "Systém pro sledování únavy řidiče." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219790.
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This diploma thesis deals with the options of image processing on mobile platforms, especially on Android operating system, and their use in a driver drowsiness detection system. The introductory part analyses the influence of drowsiness on drivers, focusing chiefly on the microsleep, and describes the already existing driver drowsiness detection systems. The thesis proceeds by the description of possibilities of image processing on mobile platforms with the emphasis on Android operating system together with the OpenCV library, known from the desktop interface. This is followed by comparison of various options of library implementation on a mobile platform. The chapter on image processing describes the algorithms for the detection of objects in the image, usable for detection of face, eyes and their posture. The practical part implements the selected methods for the Android operating system. A referential application was created to provide an explanatory demonstration of these methods on a real device. The individual methods are compared on the basis of time consumption, error rate and other factors.
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Cardoso, José Ricardo Ferreira. "Desenvolvimento de Estrutura Robótica para Aquisição e Classificação de Imagens (ERACI) de Lavoura de Cana-de-Açúcar /." Jaboticabal, 2020. http://hdl.handle.net/11449/192961.
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Orientador: Carlos Eduardo Angeli FurlaniResumo: A agricultura digital tem contribuído com a melhoria da eficiência na aplicação de insumos ou no plantio em local pré-determinado, resultando no aumento da produtividade. Nesta realidade a aplicação de técnicas de Processamento de Imagens Digitais, bem como a utilização de sistemas que utilizam a Inteligência Artificial, tem ganhado cada vez mais a atenção de pesquisadores que buscam a sua aplicação nos mais diversos meios. Com o objetivo de desenvolver um sistema robótico que utiliza um sistema de visão computacional capaz analisar uma imagem e, detectar basicamente a presença de cana-de-açúcar e planta daninha, bem como a ausência de qualquer planta, o projeto desenvolvido unificou conhecimentos sobre estas duas áreas da ciência da computação com a área de robótica e agricultura que, culminou no desenvolvimento de uma estrutura robótica com ferramentas gratuitas, como é o caso dos softwares e hardwares modulares voltados para o ensino de informática em escolas. A união de tudo isso resultou em uma estrutura de software e hardware que captura e armazena imagens em um banco de dados; além de possibilitar a classificação de imagens pelos usuários habilitados por meio de aplicativo Android. Por meio da verificação da acurácia entregue pelos algoritmos de Machine Learning, com injeção cíclica e, pela análise do tempo de resposta, foi constatado que o sistema é capaz, munido destas informações, de gerar classificadores que, remotamente são carregados pelo DRR (Dispositivo Robótic... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: Digital agriculture has contributed to improving efficiency in the application of inputs or planting in a predetermined location, resulting in increased productivity. In this reality, the application of Digital Image Processing techniques, as well as the use of systems that use Artificial Intelligence, has increasingly gained the attention of researchers who seek their application in the most diverse media. In order to develop a robotic system capable of creating a computer vision system capable of analyzing an image and basically detecting the presence of sugarcane and weed, as well as the absence of any plant, the project developed unified knowledge on these two areas of computer science with the area of robotics and agriculture, which culminated in the development of a robotic structure with free tools, such as software and modular hardware aimed at teaching computer science in schools. The combination of all this resulted in a software and hardware structure capable of allowing the capture and storage of images in a database; in addition to enabling the classification of images by users enabled through the Android application. By checking the accuracy delivered by the Machine Learning algorithms with cyclic injection and analyzing the response time, it was found that the system was able, with this information, to generate classifiers that are remotely loaded by the RRD and these, in turn, were able to classify images in sugarcane fields in real time.
Mestre
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Malm, Lukas, and Anna Phan. "Mozart2000 : Music reading and piano playing robot." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264443.
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Many industries have been transformed to better perform in today’s digital age. In this project a solution for digitalizing printed sheet music as well as automating piano playing is researched, developed and built. The project was divided into three sub-systems, the first focusing on the digitalizing of sheet music, the second on identifying and classifying the notes and the third on playing the piano. These were later combined to form a demonstrator called Mozart2000, or M2k. The result was a robot which could determine the note pitch of an arbitrary note, or note combination, written in common music notation, and furthermore play these on the piano. The algorithm is based of off finding coordinates for stafflines and notes using image processing. Programming was done in Python with some functions extracted from the library OpenCV (Open Source Computer Vision). The piano playing mechanism uses solenoids and lever arms, controlled by electrical signals from a Raspberry Pi. Due to scope in budget and time some restrictions were made. The note range for the robot was limited to one octave, meaning 8 piano keys. Moreover, other musical information such as rhythmical and coloring were overlooked and set to a predetermined value. For the digitalizing part, a camera was used, taking a snapshot of one musical bar. The final solution however can be expanded to include additional keys and music segments by replicating the existing mechanism.I detta projekt söks en lösning för digitalisering av tryckt notskrift, mot bakgrund av en ökande efterfrågan på digitala lösningar. Parallellt undersöks möjligheterna till att automatisera pianospel. För att underlätta arbetet delades projektet in i tre delsystem; det första fokuserade på digitalisering av notpapper, det andra på att hitta och identifiera noter, och det tredje på pianospelet. Delsystemen kunde därefter integreras och resulterade då i Mozart2000, M2k. Den slutgiltiga lösningen är en robot som kan bestämma tonhöjden från ett notpapper och spela dessa på ett piano. Den framtagna algoritmen bygger på att hitta koordinater för notlinjer och noter, jämföra dessa sinsemellan och tilldela dessa utgångar på en Raspberry Pi. Från dessa skickas elektriska signaler till en krets bestående av bland annat transistorer och frihjulsdioder, som i sin tur är kopplade till solenoider. Dessa solenoider kopplade till egentillverkade fingrar kommer sedan att slå an tangenterna på pianot. Eftersom projektet var begränsat i tid och budget gjordes ett antal förenklingar. Till exempel skulle Mozart2000 hålla sig till en oktav, det vill säga åtta toner. Vidare skulle rytmen vara en konstant och endast en takt skulle analyseras och spelas åt gången. Det bedöms dock möjligt att duplicera systemet för att täcka ett större notomfång och/eller fler takter.
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Yao, Yuanbin. "GPU Based Real-Time Trinocular Stereovision." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-theses/971.
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"Stereovision has been applied in many fields including UGV (Unmanned Ground Vehicle) navigation and surgical robotics. Traditionally most stereovision applications are binocular which uses information from a horizontal 2-camera array to perform stereo matching and compute the depth image. Trinocular stereovision with a 3-camera array has been proved to provide higher accuracy in stereo matching which could benefit application like distance finding, object recognition and detection. However, as a result of an extra camera, additional information to be processed would increase computational burden and hence not practical in many time critical applications like robotic navigation and surgical robot. Due to the nature of GPUÂ’s highly parallelized SIMD (Single Instruction Multiple Data) architecture, GPGPU (General Purpose GPU) computing can effectively be used to parallelize the large data processing and greatly accelerate the computation of algorithms used in trinocular stereovision. So the combination of trinocular stereovision and GPGPU would be an innovative and effective method for the development of stereovision application. This work focuses on designing and implementing a real-time trinocular stereovision algorithm with GPU (Graphics Processing Unit). The goal involves the use of Open Source Computer Vision Library (OpenCV) in C++ and NVidia CUDA GPGPU Solution. Algorithms were developed with many different basic image processing methods and a winner-take-all method is applied to perform fusion of disparities in different directions. The results are compared in accuracy and speed to verify the improvement."
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Черкас, В. Є. "Інформаційна технологія визначення змін в потокових відео методом зонування." Master's thesis, Сумський державний університет, 2021. https://essuir.sumdu.edu.ua/handle/123456789/84150.
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Розроблено інтелектуальну систему, яка зчитує відезаписи, оброляє їх, надає змогу користувачу обирати необхідну зону для дослідження на наявність руху, віднаходить періоди руху та записує знайдені дані щодо часу періодів руху в CSV файл. Проведено тестування розробки на реальних данних з камер відеоспотреження м. Суми.
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Bananga, L. A. "Information technology of autonomous drone control system design." Master's thesis, Sumy State University, 2021. https://essuir.sumdu.edu.ua/handle/123456789/86926.
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Wass, Anton, and Forsberg Eddie Löwenborg. "Augmented reality i en industriell tillverkningsprocess." Thesis, KTH, Data- och elektroteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208957.
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Med den digitalisering som sker just nu i den industriella världen väcks stor nyfikenhet på hur framtidens tekniker såsom “Augmented Reality” kan appliceras i industriella tillverkningsprocesser. Målet med examensarbetet var att undersöka om och hur AR-teknik kan utnyttjas i industrin för att förbättra nuvarande arbetsprocesser. Två prototyper utvecklades för AR-glasögonen Microsoft HoloLens och utvärderades genom att jämföra tidigare arbetssätt med nya. Testerna av prototyperna visade att effektiviteten, produktionskvalitén och rörligheten ökade för användaren till en bekostnad av sämre ergonomi.With the digitization that is happening right now in the industrial world, there is a lot of curiosity about how future technologies like Augmented Reality can be applied in industrial manufacturing processes. The aim of the thesis was to investigate whether and how augmented reality technology can be utilized in industries to improve current work processes. Two prototypes were developed for the augmented reality glasses Microsoft HoloLens and evaluated by comparing previous working methods with new ones. Tests of the prototypes showed that efficiency, production quality and mobility increased for the user at the expense of worse ergonomics.
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Jansson, Martin, and Simon Petersson. "Object detection and single-board computers : En förstudie gjord på Saab AB." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-75981.
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Saab använder sig i nuläget av ett utdaterat system för att utföra tester av deras produkter. Systemet filmar ur olika vinklar och sammanfogar videoströmmarna till en slutgiltig video, där de sedan kan analysera resultatet av produkten. Enkortsdatorer är något som på senare år har blivit mer och mer populärt, Saab vill därför undersöka om det går att ersätta det äldre systemet med enkortsdatorer och kameror.Det ska undersökas om enkortsdatorn BeagleBoard klarar av att köra objektidentifiering samtidigt som den filmar och utför operationer som videosynkning, videokodning samt sparar den synkade filmen.Undersökningen visade att BeagleBoardens processor inte är tillräckligt kraftfull för att klara av objektidentifieringen utan hårdvarustöd. Istället behöver det utföras av en dator som bearbetar filmen i efterhand och plockar ut objekt. Det har förslagits en bättre metod för att göra objektidentifieringen smartare och lärande som kommer fungera bättre i Saabs fall.Saab is currently using an old and complex system to perform tests of their products. The system is based on filming from different angles which will be merged to one film from which Saab can analyze the results of their products. Single-board computers is something that have become increasingly popular in the recent years, therefore, we are to investigate whether it is possible or not to replace the older systems with SBCs and cameras.We will also investigate whether the BeagleBoard is capable of detecting objects while filming, synchronizing, encoding and saving the video for later use.The result showed that the processor isn’t powerful enough to handle object identification without full hardware support. Instead, it needs to be performed afterwards by a computer which will identify objects in the video. A better method has been proposed to make object identification smarter and learning, which will work better in Saab’s case and their future work.
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Shenaj, Donald. "Implementazione e analisi di un sistema per il conteggio di veicoli in Python e OpenCV." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
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Scopo di questa tesi è l'implementazione e analisi di un sistema per il conteggio di veicoli, elaborando segnali video mediante la libreria OpenCV con il linguaggio di programmazione Python. È stato introdotto un sistema di tracking per migliorare le prestazioni dell'algoritmo e si è ottimizzato il software per renderlo eseguibile in tempo reale su una Raspberry. Si pensa che il sistema realizzato possa contribuire a ridurre il consumo di elettricità, ottimizzando l'illuminazione stradale in base alla condizione del traffico stimata dal sistema
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Janeček, Martin. "Soustava kamer jako stereoskopický senzor pro měření vzdálenosti v reálném čase." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220332.
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Project shows calibration stereoscopic sensor. Also describes basic methods stereo-corespodation using library OpenCV. Project contains calculations of disparity maps on CPU or graphic card(using library OpenCL).
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Fidanza, Giovanni. "Tracciamento dello sguardo tramite fotocamera frontale dello smartphone." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17884/.
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Lo scopo di questa ricerca e di creare un algoritmo per il tracciamento
approssimativo della direzione dello sguardo umano utilizzando la fotocamere di comuni smartphone.
Attualmente esistono varie tecnologie di Eye-tracking, a vari livelli di precisione, quasi sempre basate su costosi hardware dedicati.
L'obiettivo finale è quello di integrare l'algoritmo sulle app per smartphone e consentire a chi lo sta usando di essere allertato se qualcuno “sbircia” nel suo dispositivo.
L'idea di base è quella di utilizzare la fotocamera frontale dell'utente per "intercettare" ed analizzare i movimenti oculari dei i vari volti inquadrati, escludendo la faccia dell'utente mediante funzioni già presenti in Android.
L'algoritmo mira a fornire un Alert se rileva sguardi indiscreti verso il proprio smartphone e sollecitare un comportamento di protezione della privacy, ad esempio evitando di leggere dati sensibili o digitare password.
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Kallin, Clarke Semone. "Markerless Augmented Reality for Visualization of 3D Objects in the Real World." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-110901.
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This report documents the research and experiments on evaluating the possibilities of using OpenCV for developing a markerless augmented reality applications using the structure from motion algorithm. It gives a background on what augmented reality is and how it can be used and also theory about camera calibration and the structure from motion algorithm is presented. Based on the theory the algorithm was implemented using OpenCV and evaluated regarding its performance and possibilities when creating markerless augmented reality applications.
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Cederholm, Lars, and Niklas Pettersson. "Stereo Vision System for an Autonomous Robotic Platform." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-12610.
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Jaganathan, Sivakumar. "ON THE INCORPORATION OF THE PERSONALITY FACTORS INTO CROWD SIMULATION." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4113.
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Recently, a considerable amount of research has been performed on simulating the collective behavior of pedestrians in the street or people finding their way inside a building or a room. Comprehensive reviews of the state of the art can be found in Schreckenberg and Deo (2002) and Batty, M., DeSyllas, J. and Duxbury, E. (2003). In all these simulation studies, one area that is lacking is accounting for the effects of human personalities on the outcome. As a result, there is a growing emphasis on researching the effects of human personalities and adding the results to the simulations to make them more realistic. This research investigated the possibility of incorporating personality factors into the crowd simulation model. The first part of this study explored the extraction of quantitative crowd motion from videos and developed a method to compare real video with the simulation output video. Several open source programs were examined and modified to obtain optical flow measurements from real videos captured at sporting events. Optical flow measurements provide information such as crowd density, average velocity with which individuals move in the crowd, as well as other parameters. These quantifiable optical flow calculations provided a strong method for comparing simulation results with those obtained from video footage captured in real life situations. The second part of the research focused on the incorporation of the personality factors into the crowd simulation. Existing crowd models such as HelbingU-Molnár-Farkas-Vicsek (HMFV) do not take individual personality factors into account. The most common approach employed by psychologists for studying personality traits is the Big Five factors or dimensions of personality (NEO: Neuroticism, Extroversion, Openness, Agreeableness and Conscientiousness). iii In this research forces related to the personality factors were incorporated into the crowd simulation models. The NEO-based forces were incorporated into an existing HMFV simulated implemented in the MASON simulation framework. The simulation results were validated using the quantification procedures developed in the first phase. This research reports on a major expansion of a simulation of pedestrian motion based on the model (HMFV) by Helbing, D., I. J. Farkas, P. Molnár, and T. Vicsek (2002). Example of actual behavior such as a crowd exiting church after service were simulated using NEO-based forces and show a striking resemblance to actual behavior as rated by behavior scientists.Ph.D.
Other
Engineering and Computer Science
Modeling and Simulation PhD
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Genovese, Antonio. "Sperimentazione con una libreria per la decodifica di bar code in immagini." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/6434/.
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In questa tesi viene studiata la libreria zbar.h il cui compito è decodificare i barcode presenti in immagini. Per acquisire le immagini si utilizzano funzioni contenute nella libreria OpenCV. Successivamente viene creata un'interfaccia tra OpenCV e ZBar. Vengono effettuati alcuni test per verificare l'efficienza sia di ZBar e sia dell'interfaccia. Concludendo, si crea una nuova libreria in cui sono inglobate le funzioni di ZBar e l'interfaccia OpenCV-ZBar
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Eriksson, Josefine, and Lindelöf Anna. "Measuring Student Attention with Face Detection: : Viola-Jones versus Multi-Block Local Binary Pattern using OpenCV." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166416.
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The purpose of this study is to discuss and attempt to approach an answer to the question of how face detection could be used to measure attention in a lecture hall.The conclusion might help further studies in using face detection to provide teachers with tools which can be used to improve learning during lectures. Face detection in real time applications became possible in 2001 when Viola and Jones presented a new method several times faster than any previous attempt. In 2007 Liao et al. presented a method using multi-block local binary patterns (MB-LBP) for the purpose of overcoming the simplicity and limitations of the Viola-Jones method. Computer vision libraries such as OpenCV make it easy to implement such algorithms. It currently supports both the Viola-Jones algorithm and the MB-LBP algorithm. This study compared these two face detection methods to see how they perform in terms of sensitivity and precision and attempted to identified limitations of both methods when used to detect attention in a simulated lecture environment. The study was conducted using boosted algorithms and functionality provided by OpenCV. The input data consisted of a recorded simulated lecture with 6 subjects performing different poses, labeled either attention or no attention, during certain periods of time, each pose recognized from a previously recorded actual lecture as a commonly occurring pose. The most significant difference of performance identified in the study was that the MB-LBP method performed face detection in an image three times faster than for Viola-Jones which confirmed previous reported results. Both methods generated high sensitivity values for all poses, but low precision values for two of the poses.The ability of both methods to detect downward tilted faces contributed to a high number of false positives returned when subjects performed the two poses of subjects taking notes or subjects performing activities labeled as no attention. Due to the low precision values caused by this, both methods were not considered to measure attention effectively. It is therefore suggested to instead train a MB-LBP-based method for the specific task of measuring attention in a lecture hall by training it to reject downward-tilted faces and to accept only instances conforming to the chosen definition of attention.
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Dahl, Dag, and Sterne Gustaf. "En jämförelse av Eigenface- och Fisherface-metoden tillämpade i en Raspberry Pi 2." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-29795.
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Syftet med rapporten är att visa möjligheten att använda Raspberry Pi 2 i ett ansiktsigenkänningssystem. Studien redogör för prestandaskillnader mellan Eigenface och Fisherfacemetoden. Studieförfattarna har genomfört en experimentell studie enligt en kvantitativ metod där tester utgör empirin. Resultatet från testerna kommer presenteras genom diagram och påvisa möjligheten att använda Raspberry Pi 2 som hårdvara i ett ansiktsigenkänningssystem. Genom samma testutförande kommer skillnader mellan igenkänningsmetoderna att påvisas. Studien visar att Raspberry Pi 2 är en lämplig kandidat att använda för mindre ansiktsigenkänningssystem. Vidare framgår det att Fisherface-metoden är det lämpligaste valet att använda vid implementation av systemet.The purpose with this report is to demonstrate the possibility to use Raspberry Pi 2 as hardware in a face recognition system. The study will show performance differences regarding the Eigenface- and Fisherface-method. To demonstrate the possibility the authors have done tests using an experimental study and quantitative method. To review the tests and to understand the result a qualitative literature review was taken. The tests will be presented as graphs to show the possibility to use Raspberry Pi 2 as hardware in a face recognition system. The same goes for the comparison of the chosen algorithms. The work indicates that Raspberry Pi 2 is a possible candidate to use for smaller face recognition systems. There is also an indication that the Fisherface method is the better choice for face recognition.
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Svensson, Johan. "Mätning av skärgradshöjd på stål." Thesis, KTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188476.
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Idag beskärs en stålrulle inom stålindustrin i ett skärverk, stålrullarna delas tillmindre delband med dålig kontroll av skärgradshöjdens kvalitet. Stickprover tas manuelltvilket endast blir ett fåtal stickprover på en stålrulle som har 150 delband ochär 30 kilometer i längd. En hål omsändning för en stålrulle kostar upp mot en miljonkronor och har en negativ klimatpåverkan. En mjukvaruprototyp för detektering avskärgradshöjd med en referenslinje togs fram. Prototypen innehöll en ljussensor, tvåmotorer, en PC och en prototypkonstruktion. Varje uppgift i programvaran tilldeladesen egen tråd. Operativsystem, trådar och algoritmer prestanda testades för mätningav exekveringstider och periodtider. Resultatet visade att en skärgradsdetektorvar möjlig att realisera. Algoritmen för skärgradshöjd med referenslinje detekteradeskärgradshöjden där amplituden var tillräckligt stor.Today, a steel roll is cut within the steel industry in a cutting factory, the steel rollsare divided to smaller part bands with poor control of the burr height quality. Samplesis taken manually, the amount of samples is too low to know the quality of thesteel roll, the steel rolls can be divided up to 150 times and the length will be 30 kilometers. A whole resend for one steel roll costs up against a million SEK and has anegative climatic impact. One software prototype for detection of burr heights witha reference line was programmed. The prototype contained one light sensor, two motors,a PC and one prototype construction. Each task in the software was allocatedan own thread. Operating systems, threads and algorithms was performance testedfor measurement of execution times and period times. The result showed that a burrheight detector where possible to implement. The algorithm could detect burrheights that were too large related to its reference line.
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Panice, Natália Ribeiro. "Método de detecção automática de eixos de caminhões baseado em imagens." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/18/18144/tde-11122018-213600/.
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A presente pesquisa tem por objetivo desenvolver um sistema automático de detecção de eixos de caminhões a partir de imagens. Para isso, são apresentados dois sistemas automáticos: o primeiro para extração de imagens de caminhões a partir de filmagens de tráfego rodoviário feitas em seis locais de uma mesma rodovia situada no Estado de São Paulo, e o segundo, para detecção dos eixos dos caminhões nas imagens. Ambos os sistemas foram fundamentados em conceitos de Processamento de Imagens e Visão Computacional e o desenvolvimento foi feito utilizando programação em linguagem Python e as bibliotecas OpenCV e SciKit. O salvamento automático das imagens de caminhões foi necessário para a construção do banco de imagens utilizado no outro método: a detecção dos eixos dos veículos identificados. Neste estágio foram realizadas a segmentação da imagem do caminhão, a detecção propriamente dita e a classificação dos eixos. Na segmentação dos veículos, utilizou-se as técnicas de limiarização adaptativa seguida de morfologia matemática e em outra ocasião, o descritor de texturas LBP; enquanto na detecção, a Transformada de Hough. Da análise de desempenho desses métodos, a taxa de salvamento das imagens foi 69,2% considerando todos os caminhões que se enquadraram nos frames. Com relação às detecções, a segmentação das imagens dos caminhões feita utilizando limiarização adaptativa com morfologia matemática ofereceu resultados de 57,7% da detecção do total de eixos dos caminhões e 65,6% de falsas detecções. A técnica LBP forneceu, para os mesmos casos, respectivamente, 68,3% e 84,2%. O excesso de detecção foi um ponto negativo dos resultados e pode ser relacionado aos problemas do ambiente externo, geralmente intrínsecos às cenas de tráfego de veículos. Dois fatores que interferiram de maneira significativa foram a iluminação e a movimentação das folhas e galhos das árvores devido ao vento. Desconsiderando esse inconveniente, derivado dos fatores recém citados, as taxas de acerto dos dois tipos de segmentação aumentariam para 90,4% e 93,5%, respectivamente, e as falsas detecções mudariam para 66,5% e 54,7%. Desse modo, os dois sistemas propostos podem ser considerados promissores para o objetivo proposto.This research aims to develop an automatic truck axle detection system using images. Two automatic systems are presented: one for the extraction of truck images from road videos recorded in a São Paulo state highway and one for the axle detection on images. Both systems are based on Image Processing and Computational Vision techniques, with using programming in Python and OpenCV and SciKit libraries. The truck image extraction system was necessary for the creation of image base, to be used on the axle detection system. Thereunto, image segmentation, axle detection and classification on images were made. In segmentation was used adaptive threshold technique, followed by mathematical morphology and on another time, LBP texture descriptors; for detection, was used Hough Transform. Performance analysis on these methods wielded 69.2% on image save rate, on trucks entirely framed on the image. About axle detection, the truck image segmentation using a combination of adaptive threshold and mathematical morphology wielded 57.7% on axle detection, whilst achieving 65.6% of false detection. Using LBP wielded, on the same images, 68.3% on axle detection and 84.2% of false detection. These excesses was a negative result and can be related to intrinsic issues on the external road traffic environment. Two main factors affected the result: lighting condition changes and the movement of tree leaves and branches. Disregarding these two factors, the proposed system had 90.4% axle truck detection rate using adaptive threshold and mathematical morphology and 93.5% using LBP, and the false detection, changed for 66.5% e 54.7%. Thus, both proposed systems are considered promising.
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Sun, Ruiwen. "Detecting Faulty Tape-around Weatherproofing Cables by Computer Vision." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272108.
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More cables will be installed owing to setting up more radio towers when it comes to 5G. However, a large proportion of radio units are constructed high in the open space, which makes it difficult for human technicians to maintain the systems. Under these circumstances, automatic detections of errors among radio cabinets are crucial. Cables and connectors are usually covered with weatherproofing tapes, and one of the most common problems is that the tapes are not closely rounded on the cables and connectors. This makes the tape go out of the cable and look like a waving flag, which may seriously damage the radio systems. The thesis aims at detecting this flagging-tape and addressing the issues. This thesis experiments two methods for object detection, the convolutional neural network as well as the OpenCV and image processing. The former uses YOLO (You Only Look Once) network for training and testing, while in the latter method, the connected component method is applied for the detection of big objects like the cables and line segment detector is responsible for the flagging-tape boundary extraction. Multiple parameters, structurally and functionally unique, were developed to find the most suitable way to meet the requirement. Furthermore, precision and recall are used to evaluate the performance of the system output quality, and in order to improve the requirements, larger experiments were performed using different parameters. The results show that the best way of detecting faulty weatherproofing is with the image processing method by which the recall is 71% and the precision reaches 60%. This method shows better performance than YOLO dealing with flagging-tape detection. The method shows the great potential of this kind of object detection, and a detailed discussion regarding the limitation is also presented in the thesis.Fler kablar kommer att installeras på grund av installation av fler radiotorn när det gäller 5G. En stor del av radioenheterna är dock konstruerade högt i det öppna utrymmet, vilket gör det svårt för mänskliga tekniker att underhålla systemen. Under dessa omständigheter är automatiska upptäckter av fel bland radioskåp avgörande. Kablar och kontakter täcks vanligtvis med väderbeständiga band, och ett av de vanligaste problemen är att banden inte är rundade på kablarna och kontakterna. Detta gör att tejpen går ur kabeln och ser ut som en viftande flagga, vilket allvarligt kan skada radiosystemen. Avhandlingen syftar till att upptäcka detta flaggband och ta itu med frågorna. Den här avhandlingen experimenterar två metoder för objektdetektering, det invändiga neurala nätverket såväl som OpenCV och bildbehandling. Den förstnämnda använder YOLO (You Only Look Once) nätverk för träning och testning, medan i den senare metoden används den anslutna komponentmetoden för detektering av stora föremål som kablarna och linjesegmentdetektorn är ansvarig för utvinning av bandbandgränsen. Flera parametrar, strukturellt och funktionellt unika, utvecklades för att hitta det mest lämpliga sättet att uppfylla kravet. Dessutom används precision och återkallande för att utvärdera prestandan för systemutgångskvaliteten, och för att förbättra kraven utfördes större experiment med olika parametrar. Resultaten visar att det bästa sättet att upptäcka felaktigt väderbeständighet är med bildbehandlingsmetoden genom vilken återkallelsen är 71% och precisionen når 60%. Denna metod visar bättre prestanda än YOLO som hanterar markering av flaggband. Metoden visar den stora potentialen för denna typ av objektdetektering, och en detaljerad diskussion om begränsningen presenteras också i avhandlingen.
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Potros, Bashar. "Framställning av mätmetod för att upptäcka defekta luftmunstycken : Framställa en säker och tillförlitlig mätmetod för att mäta mängd vatten i 50 provrör." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-14965.
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För att upptäcka defekta luftmunstycken har Ecco FinishingABi Skara tagit fram en ny provutrustning som ska ersätta en otillförlitlig och osäker befintlig provmaskin. Ecco Fi-nishing AB vill hitta en tillförlitlig och säker mätmetod som ska mäta mängd vatten i 50 provrör. Examensarbetets övergripande mål är att hitta en noggrann och repeterbarmätmetod för nivåmätning av vätska i provrören. Två mätmetoder utvärderades som är mest lämpliga för nivåmätningen, visionsystem och mätning genom vägning. Anledningen till att valet ham-nade på dessa två mätmetoder är provutrustningens provrör, dels att det är många mätpunkter och för att det är små provrör. Det gjordes tjugo experiment för visionsystem och tjugoex-periment för vägningsmetodför att utvärdera och beskriva för -och nackdelar. Experimenten av visionsystem och vägning gjordes först i laborationsfas för att sedan testas på företagets befintliga provutrustning. Resultaten av mätningar sparades i ett Excel-ark som användes för att utvärdera insamlade data. Utvärderingarna jämfördes mot uppsatta mål, tillförlitlighet, noggrannhet, repeterbarhet, automatisk rapportering av resultat och tid för mätningen. Vis-ionsystem rekommenderas för fortsatt arbete och implementation på den befintliga provut-rustningen.To detect defective air nozzles, Ecco Finishing AB in Skara has developed a new test equip-ment to replace an unreliable and uncertain existing test machine. Ecco Finishing AB wants to find a reliable and safe measurement method that will measure the amount of water in 50 test tubes. The overall goal of the thesis is to find a precise and repeatable measurement method for level measurement of fluid in the test tubes. Two measurement methods were evaluated that are most suitable for level measurement, vision systems and measurement by weighing. The reason for the choice of these two measurement methods is the test tubes of the test equipment, and that there are many measuring points and because of the small test tubes. Twenty experiments for vision systems and twenty experiments for weighingmethodwere made to evaluate and describe pros and cons. The experiments of vision systems and weighing were first made in the laboratory phase and then tested on the company's existing test equipment. The results of measurements were saved in an Excel sheet used to evaluate collected data. The evaluations were compared to set goals, reliability, accuracy, repeatabil-ity, automatic reporting of results and time of measurement. Vision systems are recom-mended for continued work and implementation on the existing test equipment
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Hassan, Waleed, and Martin Hellström. "Realtidsövervakning av multicastvideoström." Thesis, KTH, Data- och elektroteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209022.
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Den enorma ökningen av multicasttjänster har visat begränsningarna hos traditionella nätverkshanteringsverktyg vid multicastkvalitetsövervakning. Det behövs någon annan form av övervakningsteknik som inte är en hårdvaruinriktad lösning så som ökad länkgenomströmmning, buffertlängd och kapacitet för att förbättra kundupplevelsen. I rapporten undersöks användningen av biblioteken FFmpeg, och OpenCV samt no-reference image quality assessemnt algoritmen BRISQUE för att förbättra tjänstekvaliteten och kundupplevelsen. Genom att upptäcka kvalitetsbrister hos bildrutor samt bitfel i videoströmmen kan QoS och QoE förbättras. Uppgiftens ändamål är att i realtid detektera avvikelser i bildkvalitet och bitfel i en multicastvideoström för att sedan notifiera tjänsteleverantören med hjälp av SNMP traps. Undersökningen visar positiva resultat med en hybridlösning med användning av både BRISQUE och FFmpeg då båda ensamma inte är tillräckligt anpassade för multimediaövervakning. FFmpeg har möjligheten att detektera avkodningsfel som oftast beror på allvarliga bitfel, och BRISQUE algoritmen utvecklades för att analysera bilder och bestämma bildkvaliteten. Enligt testresultaten kan BRISQUE användas för multicastvideoanalysering eftersom att den subjektiva bildkvaliteten kan bestämmas med god pålitlighet. Kombinationen av dessa metoder har visat bra resultat men behöver undersökas mer för användning av multicastövervakning.The enormous increase in multicast services has shown the limitations of traditional network management tools in multicast quality monitoring. There is a need for new monitoring technologies that are not hardware-based solutions such as increased link throughput, buffer length and capacity to enhance the quality of experience. This paper examines the use of FFmpeg, and OpenCV as well the no-reference image quality assessment algorithm BRISQUE to improve the quality of service as well as the quality of experience. By detecting image quality deficiencies as well as bit errors in the video stream, the QoS and QoE can be improved. The purpose of this project was to develop a monitoring system that has the ability to detect fluctuations in image quality and bit errors in a multicast video stream in real time and then notify the service provider using SNMP traps. The tests performed in this paper shows positive results when using the hybrid solution proposed in this paper, both BRISQUE and FFmpeg alone are not sufficiently adapted for this purpose. FFmpeg has the ability to detect decoding errors that usually occurs due to serious bit errors and the BRISQUE algorithm was developed to analyse images and determine the subjective image quality. According to the test results BRISQUE can be used for multicast video analysis because the subjective image quality can be determined with good reliability. The combination of these methods has shown good results but needs to be investigated and developed further.
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Silva, Jonas Fernandes da. "Uma solução de baixo custo para o processamento de imagens aéreas obtidas por Veículos Aéreos Não Tripulados." Universidade Federal da Paraíba, 2016. http://tede.biblioteca.ufpb.br:8080/handle/tede/9262.
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Currently, unmanned aerial vehicles (UAV) are increasingly used to aid the various tasks around the world. The popularization of this equipment associated with the advancement of technology, particularly the miniaturization of processors, extend their functionalitys. In agricultural applications, these devices allow monitoring of production by capturing aerial images, for which are processed and identified areas of interest through specific software. The research proposes a low-cost solution capable of processing aerial images obtained by non-metric digital cameras coupled to UAV to identify gaps in plantations or estimate levels of environmental degradation, which can be deployed in small computers and low power consumption. Embedded systems coupled in UAV allow perform processing in real time, which contributes to a preventive diagnosis, reduces the response time and can avoid damages in the crop. The algorithm used is based on watershed, while the second algorithm uses classification techniques based on the 1-Nearest Neighbor (1-NN). Are used the embedded systems DE2i-150 and Intel Edison, both x86 architecture, and Raspberry Pi 2 of ARM architecture. Moreover, the technique 1-NN showed higher tolerance to lighting problems, however, require more processing power compared to the algorithm based on watershed. The results show that the proposed system is an efficient and relatively low-cost solution compared to traditional means of monitoring and can be coupled in a UAV to perform the processing during the flight.
Atualmente, veículos aéreos não tripulados (VANT) são cada vez mais utilizados no auxílio a diversas tarefas em todo o mundo. A popularização destes equipamentos associada ao avanço da tecnologia, sobretudo a miniaturização de processadores, ampliam suas funcionalidades. Em aplicações agrícolas, estes equipamentos permitem o monitoramento da produção por meio da captação de imagens aéreas, a partir dos quais são processadas e identificadas áreas de interesse por meio de softwares específicos. A pesquisa propõe uma solução de baixo custo capaz de processar imagens aéreas obtidas por câmeras digitais não métricas acopladas a VANT para identificar falhas em plantações ou estimar níveis de degradação ambiental, os quais possam ser implantados em computadores de pequeno porte e baixo consumo, conhecido como sistemas embarcados. Plataformas embarcadas acopladas a VANT permitem realizar o processamento em tempo real, que contribui para um diagnóstico preventivo, reduz o tempo de resposta e pode evitar prejuízos na lavoura. O algoritmo inicialmente avaliado é baseado em watershed, enquanto que o segundo algoritmo proposto faz uso de técnicas de classificação baseada no 1-vizinho mais próximo (1-NN). Utilizam-se os sistemas embarcados DE2i-150 e Intel Edison, ambos de arquitetura x86, e a plataforma Raspberry Pi 2 de arquitetura ARM. Em relação ao processamento das imagens são alcançados níveis de acurácia em torno de 90%, com uso do algoritmo baseado em 1-NN. Além disso, a técnica 1-NN apresentou maior tolerância aos problemas de luminosidade, em contrapartida, demandam maior poder de processamento quando comparados com o algoritmo baseado em watershed. Os resultados mostram que o sistema proposto é uma solução eficiente e de custo relativamente baixo em comparação com os meios tradicionais de monitoramento e pode ser acoplada em um VANT para realizar o processamento durante o voo.
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Cöster, Jonatan, and Michael Ohlsson. "Human Attention : The possibility of measuring human attention using OpenCV and the Viola-Jones face detection algorithm." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166584.
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The question of whether an audience is focused and attentive can be of great importance. Research shows that a main concern during lectures is the varying level of attention from the students. Getting real time feedback on the students attention could give the lecturer an insight into what can be improved in terms of the material being presented. One potential way to get this feedback is to have a face detection algorithm to measure when someone is paying attention. The objective of the study is to investigate if it is possible to measure a person’s attention in a controlled environment using the OpenCV programming library and the Viola-Jones algorithm. In order to measure if someone was paying attention, a definition of attention was required. It is obvious to humans when someone is paying attention. However, this is not the case for a computer. A data set consisting of pictures of attentive and inattentive subjects was used to evaluate whether the software could be used to measure attention. The results of the study showed that OpenCV had an almost perfect detection rate with few false positives. The conclusion is therefore that the OpenCV programming library could be used to measure attention in a controlled environment. However, due to the limited scope of the study, further investigations are required in order to use it in a real-world application.
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Cunha, André Luiz Barbosa Nunes da. "Sistema automático para obtenção de parâmetros do tráfego veicular a partir de imagens de vídeo usando OpenCV." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18144/tde-19112013-165611/.
Full textAbstract:
Esta pesquisa apresenta um sistema automático para extrair dados de tráfego veicular a partir do pós-processamento de vídeos. Os parâmetros macroscópicos e microscópicos do tráfego são derivados do diagrama espaço-tempo, que é obtido pelo processamento das imagens de tráfego. A pesquisa fundamentou-se nos conceitos de Visão Computacional, programação em linguagem C++ e a biblioteca OpenCV para o desenvolvimento do sistema. Para a detecção dos veículos, duas etapas foram propostas: modelagem do background e segmentação dos veículos. Uma imagem sem objetos (background) pode ser determinada a partir das imagens do vídeo através de vários modelos estatísticos disponíveis na literatura especializada. A avaliação de seis modelos estatísticos indicou o Scoreboard (combinação de média e moda) como o melhor método de geração do background atualizado, por apresentar eficiente tempo de processamento de 18 ms/frame e 95,7% de taxa de exatidão. A segunda etapa investigou seis métodos de segmentação, desde a subtração de fundo até métodos de segmentação por textura. Dentre os descritores de textura, é apresentado o LFP, que generaliza os demais descritores. Da análise do desempenho desses métodos em vídeos coletados em campo, conclui-se que o tradicional método Background Subtraction foi o mais adequado, por apresentar o melhor tempo de processamento (34,4 ms/frame) e a melhor taxa de acertos totais com 95,1% de média. Definido o método de segmentação, foi desenvolvido um método para se definir as trajetórias dos veículos a partir do diagrama espaço-tempo. Comparando-se os parâmetros de tráfego obtidos pelo sistema proposto com medidas obtidas em campo, a estimativa da velocidade obteve uma taxa de acerto de 92,7%, comparado com medidas de velocidade feitas por um radar; por outro lado, a estimativa da taxa de fluxo de tráfego foi prejudicada por falhas na identificação da trajetória do veículo, apresentando valores ora acima, ora abaixo dos obtidos nas coletas manuais.This research presents an automatic system to collect vehicular traffic data from video post-processing. The macroscopic and microscopic traffic parameters are derived from a space-time diagram, which is obtained by traffic image processing. The research was based on the concepts of Computer Vision, programming in C++, and OpenCV library to develop the system. Vehicle detection was divided in two steps: background modeling and vehicle segmentation. A background image can be determined from the video sequence through several statistical models available in literature. The evaluation of six statistical models indicated Scoreboard (combining mean and mode) as the best method to obtain an updated background, achieving a processing time of 18 ms/frame and 95.7% accuracy rate. The second step investigated six segmentation methods, from background subtraction to texture segmentation. Among texture descriptors, LFP is presented, which generalizes other descriptors. Video images collected on highways were used to analyze the performance of these methods. The traditional background subtraction method was found to be the best, achieving a processing time of 34.4 ms/frame and 95.1% accuracy rate. Once the segmentation process was chosen, a method to determine vehicle trajectories from the space-time diagram was developed. Comparing the traffic parameters obtained by the proposed system to data collected in the field, the estimates for speed were found to be very good, with 92.7% accuracy, when compared with radar-measured speeds. On the other hand, flow rate estimates were affected by failures to identify vehicle trajectories, which produced values above or below manually collected data.