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Relevant bibliographies by topics / Canny's edge detection

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Academic literature on the topic 'Canny's edge detection'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 June 2025

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Journal articles on the topic "Canny's edge detection"

1

Agrawal, Himangi, and Krish Desai. "CANNY EDGE DETECTION: A COMPREHENSIVE REVIEW." International Journal of Technical Research & Science 9, Spl (2024): 27–35. http://dx.doi.org/10.30780/specialissue-iset-2024/023.

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Canny edge detection is a widely employed technique in image processing known for its effectiveness in identifying and highlighting edges within digital images. Because of its excellent performance, the Canny Edge Detector is one of the most used edge detection algorithms. For several image processing techniques, including image enhancement, image segmentation, tracking, and image/video coding, edge detection serves as a preliminary step. Compared to the Sobel algorithm, Canny's edge detection approach yields much lower memory requirements, reduced latency, and enhanced throughput without sacrificing edge detection performance. This paper provides a comprehensive review of canny edge algorithm, elucidating each step. In this paper, the canny edge algorithm is implemented on an image as well as in real time using MATLAB and its Simulink model. We have also performed high level synthesis of the proposed algorithm using HDL coder.

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HUSSAIN, MUHAMMAD, TURGHUNJAN ABDUKIRIM, and YOSHIHIRO OKADA. "WAVELET-BASED EDGE DETECTION IN DIGITAL IMAGES." International Journal of Image and Graphics 08, no. 04 (2008): 513–33. http://dx.doi.org/10.1142/s0219467808003210.

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This paper proposes a wavelet based multilevel edge detection method that exploits spline dyadic wavelets and a frame work similar to that of Canny's edge detector.2 Using the recently proposed dyadic lifting schemes by Turghunjan et al.1 spline dyadic wavelet filters have been constructed, which are characterized by higher order of regularity and have the potential of better inherent noise filtering and detection results. Edges are determined as the local maxima in the subbands at different scales of the dyadic wavelet transform. Comparison reveals that our method performs better than Mallat's and Canny's edge detectors.

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Luh Putu Risma Noviana, I Putu Eka Indrawan, and Gde Iwan Setiawan. "ANALYSIS OF CANNY EDGE DETECTION METHOD FOR FACIAL RECOGNITION IN DIGITAL IMAGE PROCESSING." Jurnal Manajemen dan Teknologi Informasi 15, no. 2 (2024): 29–34. http://dx.doi.org/10.59819/jmti.v15i2.4107.

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The document explores the application of the Canny Edge Detection method in facial recognition systems, specifically for identifying edge patterns in digital images. In the context of technological advancements, the focus is on enhancing data processing through efficient image analysis techniques. The research addresses how different edge detection methods, including Roberts, Prewitt, Sobel, and Canny, function, with the latter being highlighted for its superior ability to minimize error and deliver accurate edge detection results. The study outlines the development of a system designed to identify optimal edge detection parameters using the Canny method, focusing on facial images captured from the front. The system is limited to edge identification in such images, and performance is measured using a correlation coefficient. The process involves several technical steps, such as pre-processing the image (grayscale conversion and noise reduction) and using Gaussian filters and hysteresis thresholding to refine the detection. The research's ultimate aim is to optimize Canny's performance for identifying edges, contributing to advancements in facial recognition technology.

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Latifa Khoirani, Rino Ariansyah, and Supiyandi Supiyandi. "Aplikasi Pengolahan Citra Untuk Peningkatan Deteksi Tepi Melalui Segmentasi Citra." Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer 2, no. 3 (2024): 196–203. http://dx.doi.org/10.61132/mars.v2i3.191.

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An important digital image processing is image segmentation, which separates objects from the background for further analysis. One segmentation technique is edge detection, which looks for boundaries between areas of different brightness. This article compares four edge detection methods: Roberts, Prewitt, Sobel, and Canny. The results show that, despite requiring more complex computations, Canny's method produces the sharpest and best connected edges; Sobel and Prewitt's method, on the other hand, is faster and simpler than Roberts' method, but is less effective in dealing with noise and often produces edges that are not connected to the plane. The choice of edge detection method depends on the application. Sobel and Prewitt are good for speed and stability, and Roberts is suitable for fast processing of images with minimal noise.

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Rachitha, M. Raikar, Vasanth Kavitha, and NR Deepak. "Road Detection Using Lane Detection Algorithms with Noise and Edge Detection Techniques." Recent Trends in Data Knowledge Discovery and Data Mining, no. 1 (February 14, 2025): 1–9. https://doi.org/10.5281/zenodo.14869492.

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<em>Road fault detection is an essential part of modern vehicle systems. Particularly in real-time vehicular ad hoc networks (VANETs), this study addresses the limitations of existing fault detection algorithms. This often presents lower performance in noisy and adverse environments such as fog, powder, shadows, potholes, oil slicks and tire skid marks. To overcome these challenges, We have implemented and evaluated advanced edge detection techniques. These techniques, which include Laplacian, Sobel, and Canny edge detection, are used on previously processed road photos. It focuses on minimizing the effect of noise on the detection process and isolating regions of interest (ROI). Comparative analysis draws attention to each technique's advantages and disadvantages. In noisy environments, Canny's edge detection performs better in terms of accuracy and resilience. The foundation for enhancing error detection systems is provided by these results. As a result, autonomous driving technology is more dependable and safer.</em>

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Yu, Zhongdang, and Hamid Reza Karimi. "Edge Detector Design Based on LS-SVR." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/419792.

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For locating inaccurate problem of the discrete localization criterion proposed by Demigny, a new criterion expression of “good localization” is proposed. Firstly, a discrete expression of good detection and good localization criterion of two dimension edge detection operator is employed, and then an experiment to measure optimal parameters of two dimension Canny's edge detection operator is introduced after. Moreover, a detailed performance comparison and analysis of two dimension optimal filter obtained via utilizing tensor product for one dimension optimal filter are provided which can prove that least square support vector regression (LS-SVR) is a smoothness filter and give the construct method of the derivate operator. This paper uses LS-SVR as the object function constructor and then realizes the approximation of two dimension optimal edge detection operator. This paper proposes the utility method of using singleness operator to realize multiscale edge detection by referencing the multiscale analysis technology of the wavelets theory. Experiment shows that the method has utility and efficiency.

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MYAKININ, OLEG O., DMITRY V. KORNILIN, IVAN A. BRATCHENKO, VALERIY P. ZAKHAROV, and ALEXANDER G. KHRAMOV. "NOISE REDUCTION METHOD FOR OCT IMAGES BASED ON EMPIRICAL MODE DECOMPOSITION." Journal of Innovative Optical Health Sciences 06, no. 02 (2013): 1350009. http://dx.doi.org/10.1142/s1793545813500090.

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In this paper, the new method for OCT images denoizing based on empirical mode decomposition (EMD) is proposed. The noise reduction is a very important process for following operations to analyze and recognition of tissue structure. Our method does not require any additional operations and hardware modifications. The basics of proposed method is described. Quality improvement of noise suppression on example of edge-detection procedure using the classical Canny's algorithm without any additional pre- and post-processing operations is demonstrated. Improvement of raw-segmentation in the automatic diagnostic process between a tissue and a mesh implant is shown.

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S, Britto Ramesh Kumar, and Bhuvaneshwari A. "AN EFFICIENT BRITWARI TECHNIQUE TO ENHANCE CANNY EDGE DETECTION ALGORITHM USING DEEP LEARNING." ICTACT Journal on Soft Computing 12, no. 3 (2022): 2634–39. http://dx.doi.org/10.21917/ijsc.2022.0377.

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Artificial Intelligence edge detection refers to a set of mathematical techniques used to recognize digital image locations. The picture brightness plays a vital role in detecting dissimilarities and making decisions. Edges are the sharp changes in pictures with respect to the brightness and are commonly categorized into a collection of curved line segments. The main focus of this paper is to find sharp corner edges and the false edges present in the MRI images. The canny edge algorithm is a popular method for detecting these types of edges. The traditional canny edge detection technique has various issues that are discussed in this paper. This study analyses the canny edge algorithm and enhances the smoothing filter, pixel identifier, and feature selection. The proposed Britwari technique, Tabu Search Heuristic Pattern Identifier (TSHPI) enhances the edge detection using SUSAN Filter. Feature Selection is performed to improvise the canny edge method. Deep Learning algorithm is used for classification of pre-trained neural networks to find a greater number of edge pixels. The implementation results show that the Britwari proposed technique (SUSAN Filter Tabu Search Heuristic Pattern Identifier Hill Climbing) reached better accuracy than the traditional Canny Edge Detection algorithms. The results produced better feature set selection using edge detection in MRI images.

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Sitanggang, Sarinah, and Paska Marto Hasugian. "Image Edge Detection for Batak Ulos Motif Recognition using Canny Operators." Login : Jurnal Teknologi Komputer 18, no. 01 (2024): 137–54. https://doi.org/10.58471/login.v18i01.42.

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Batak ulos is one of the handicrafts originating from North Sumatra. In Batak Ulos, there are various kinds of motifs that are characteristic of these ulos. One way to find out the type of ulos is by knowing the motives found on the ulos. For that we need a system that can detect ulos and then can recognize these ulos. The system was built using the canny edge detection method proposed by Jhon Canny in 1986, and is known as the optimal edge detection operator. Canny operator is one of edge detection which is very good in detecting image edges. Canny operators have met the criteria in detecting, namely detecting very well, responding well and localizing well and clearly. The system built also uses the C # programming language in Microsoft Visual Studio 2010.

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Jayasree, M., K. Narayanan N, V. Kabeer, and C. R. Arun. "An Enhanced Block Based Edge Detection Technique Using Hysteresis Thresholding." Signal & Image Processing : An International Journal (SIPIJ) 9, no. 2 (2019): 15–26. https://doi.org/10.5281/zenodo.3248683.

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Edge detection is a crucial step in various image processing systems like computer vision , pattern recognition and feature extraction. The Canny edge detection algorithm even though exhibits high accuracy, is computationally more complex compared to other edge detection techniques. A block based distributed edge detection technique is presented in this paper, which adaptively finds the thresholds for edge detection depending on block type and the distribution of gradients in each block. A novel method of computation of high threshold has been proposed in this paper. Block-based hysteresis thresholds are computed using a non uniform gradient magnitude histogram. The algorithm exhibits remarkably high edge detection accuracy, scalability and significantly reduced computational time. Pratt’s Figure of Merit quantifies the accuracy of the edge detector, which showed better values than that of original Canny and distributed Canny edge detector for benchmark dataset. The method detected all visually prominent edges for diverse block size.

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Dissertations / Theses on the topic "Canny's edge detection"

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Zhu, Yuan. "Extraction of Linear Features Based on Beamlet Transform." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1301616331.

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Němec, Zbyšek. "Derichův detektor hran." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-235475.

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This thesis presents the Deriche edge detector as an interesting alternative to the commonly used edge detectors. The Deriche edge detector's design is presented to the reader as well as its strengths and weaknesses. Performance issues of the Deriche edge detector are described in comparison with the Canny edge detector together with recommendations for using the Deriche detector. Finally, edge detection quality of the Deriche edge detector is compared to the Canny edge detector using robust subjective evaluation method.

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Fendrich, Vítězslav. "Zařízení varovného systému pro udržení vozidla v jízdním pruhu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400535.

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This thesis adresses designing a device that detects lane departure of a vehicle via a video feed from a camera module. This device is intended to be attached onto the windshield of the vehicle. The initial part of the thesis will cover the current methods of lane departure detection through a video feed. In the following part the selection of suitable hardware, specifically the latest model of a Raspberry Pi, has been made. Afterwards a suitable container for the aforementioned hardware has been designed and created using a 3D printer. Subsequently an appropriate LDWS algorithm is chosen and designed. In the next part, the range and parameters of a testing database through which the proper functionality of the device will be tested on are chosen. The final part of the thesis contains evaluation of the success rate of detection via the acquired database.

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Shi, Changgui. "An implementation of the canny edge detector." Virtual Press, 1992. http://liblink.bsu.edu/uhtbin/catkey/834519.

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Labaj, Tomáš. "Detekce křivek v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236653.

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This thesis deals with curve detection in images. First, current methods used in this area of image processing are summarized and described. Main topic of this thesis is a comparison of methods of parametric curve detection, such as Hough transformation and RANSAC-based methods. These methods are compared according to several criteria which are the most important for precise edge detection.

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Zavistanavičiūtė, Rasa. "Object detection algorithms analysis and implementation for augmented reality system." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2012~D_20131105_093556-36296.

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Object detection is the initial step in any image analysis procedure and is essential for the performance of object recognition and augmented reality systems. Research concerning the detection of edges and blobs is particularly rich and many algorithms or methods have been proposed in the literature. This master‟s thesis presents 4 most common blob and edge detectors, proposes method for detected numbers separation and describes the experimental setup and results of object detection and detected numbers separation performance. Finally, we determine which detector demonstrates the best results for mobile augmented reality system.<br>Objektų aptikimas yra pagrindinis žingsnis vaizdų analizės procese ir yra pagrindinis veiksnys apibrėžiantis našumą objektų atpažinimo ir papildytosios realybės sistemose. Literatūroje gausu metodų ir algoritmų aprašančių sričių ir ribų aptikimą. Šiame magistro laipsnio darbe aprašomi 4 dažniausiai naudojami sričių ir ribų aptikimo algoritmai, pasiūlomas metodas aptiktų skaičių atskyrimo problemai išspręsti. Pateikiami atliktų eksperimentų rezultatai, palyginmas šių algoritmų našumas. Galiausiai yra nustatoma, kuris iš jų yra geriausias.

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Larsson, Mathias. "Machine vision for finding a joint to guide a welding robot." Thesis, University West, Department of Engineering Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-1783.

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<p>This report contains a description on how it is possible to guide a robot along an edge, by using a camera mounted on the robot. If stereo matching is used to calculate 3Dcoordinates of an object or an edge, it requires two images from different known positions and orientations to calculate where it is. In the image analysis in this project, the Canny edge filter has been used. The result from the filter is not useful directly, because it finds too many edges and it misses some pixels. The Canny edge result must be sorted and finally filled up before the final calculations can be started. This additional work with the image decreases unfortunately the accuracy in the calculations. The accuracy is estimated through comparison between measured coordinates of the edge using a coordinate measuring machine and the calculated coordinates. There is a deviation of up to three mm in the calculated edge. The camera calibration has been described in earlier thesis so it is not mentioned in this report, although it is a prerequisite of this project.</p>

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Homola, Antonín. "Detekce šířky papilární linie u otisku prstu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236952.

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This work outlines a method of detection of the papillary line width in fingerprints. This method is one of the possible methods of liveness detection. The first part of the work with deals defining of the fingerprint, attacks on today's systems and possibilities to improve security. The next section detection describes of the papillary line width. During the process of resolving, the first thing to do was to start operation of the scanning device and to read the database for tests and experiments. An independent application was created on this purpose. Further, there were projected methods for detection and measuring of the papillary line width. Use of the Canny edge detector with the Sobel operator and the Gaussian filter proved the best. Then, there is described implementation of individual methods. The next part of the work describes and assesses the results of the tests. The last chapter summarizes the work and proposes further possibilities of development.

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Beneš, Radek. "Využití metod zpracování signálů pro zvýšení bezpečnosti automobilové dopravy." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218105.

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This diploma thesis deals with the issue of the recognition of road signs in the video sequence. Such systems increase the traffic safety and are implemented by major car factories in the manufactured cars (Opel, BMW). First, the motivation for the utilisation of these systems is presented, followed by the survey of the current state of the art methods. Finally, a specific road-sign detection method is chosen and described in detail. The method uses advanced techniques of signal processing. Segmentation method in color space is used for sign detection and subsequent classification is accomplished by linear classification with optional use of PCA method. In addition, the method contains the prediction of road sign positions based on Kalman filtering. Implemented system yields relatively accurate results and overall analysis and discussion is enclosed.

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Vannucci, Maria Chiara. "Algoritmi di segmentazione di immagini mediche." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10878/.

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Nell'ambito dell'elaborazione delle immagini, si definisce segmentazione il processo atto a scomporre un'immagine nelle sue regioni costituenti o negli oggetti che la compongono. Ciò avviene sulla base di determinati criteri di appartenenza dei pixel ad una regione. Si tratta di uno degli obiettivi più difficili da perseguire, anche perché l'accuratezza del risultato dipende dal tipo di informazione che si vuole ricavare dall'immagine. Questa tesi analizza, sperimenta e raffronta alcune tecniche di elaborazione e segmentazione applicate ad immagini digitali di tipo medico. In particolare l'obiettivo di questo studio è stato quello di proporre dei possibili miglioramenti alle tecniche di segmentazione comunemente utilizzate in questo ambito, all'interno di uno specifico set di immagini: tomografie assiali computerizzate (TAC) frontali e laterali aventi per soggetto ginocchia, con ivi impiantate protesi superiore e inferiore. L’analisi sperimentale ha portato allo sviluppo di due algoritmi in grado di estrarre correttamente i contorni delle sole protesi senza rilevare falsi punti di edge, chiudere eventuali gap, il tutto a un basso costo computazionale.

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Book chapters on the topic "Canny's edge detection"

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Mokrzycki, Wojciech, and Marek Samko. "Canny Edge Detection Algorithm Modification." In Computer Vision and Graphics. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33564-8_64.

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Cheng, You-e. "An improved Canny Edge Detection Algorithm." In Recent Advances in Computer Science and Information Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25766-7_73.

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Ma, Xiaoju, Bo Li, Ying Zhang, and Ming Yan. "The Canny Edge Detection and Its Improvement." In Artificial Intelligence and Computational Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33478-8_7.

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Mishra, Satyam, and Le Trung Thanh. "SATMeas - Object Detection and Measurement: Canny Edge Detection Algorithm." In Artificial Intelligence and Mobile Services – AIMS 2022. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23504-7_7.

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Murali, Gunji Bala, V. Santosh Kumar, Dibya Narayan Behera, Kapil Kumar Mohanta, Omkar Tulankar, and Sanketh S. Salimath. "Pothole Detection on Roads Using Canny Edge Detection Algorithm." In Applications of Computational Methods in Manufacturing and Product Design. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0296-3_60.

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Perfilieva, Irina, Petra Hodáková, and Petr Hurtík. "F 1-transform Edge Detector Inspired by Canny’s Algorithm." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31709-5_24.

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Karande, Kailash Jagannath, and Sanjay Nilkanth Talbar. "Canny Edge Detection for Face Recognition Using ICA." In Independent Component Analysis of Edge Information for Face Recognition. Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1512-7_2.

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Ojashwini, R. N., R. Gangadhar Reddy, R. N. Rani, and B. Pruthvija. "Edge Detection Canny Algorithm Using Adaptive Threshold Technique." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5679-1_45.

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Li, Jun, and Sheng Ding. "A Research on Improved Canny Edge Detection Algorithm." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23223-7_13.

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Senthilkumar, K. K., E. Avantika, B. Gayathri, and Vaithiyanathan Dhandapani. "VLSI Implementation of Reconfigurable Canny Edge Detection Algorithm." In Big Data Analytics in Astronomy, Science, and Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-58502-9_7.

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Conference papers on the topic "Canny's edge detection"

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Zhang, Hongpeng, Chang Liu, Liangjie Feng, and Yang Yu. "Improved Canny Edge Detection Algorithm." In 2024 9th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE, 2024. https://doi.org/10.1109/iciibms62405.2024.10792784.

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Huan, Zhang, Wang Yaxin, Wang Shuang, Liu Zhihao, Chen Panyu, and Wang Fangjuan. "FPGA-based Improved Canny Edge Detection System." In 2024 IEEE 4th International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA). IEEE, 2024. https://doi.org/10.1109/iciba62489.2024.10867861.

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Chai, Zhengtong. "Nighttime Respiration Detection Based on Improved Canny Edge Detection." In 2025 5th International Conference on Sensors and Information Technology (ICSI). IEEE, 2025. https://doi.org/10.1109/icsi64877.2025.11009481.

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Wang, Desheng, Yawen Lin, Yue Sun, Min Zhang, Yulong Sun, and Weiguo Lin. "Cigarette strip defect detection based on Canny edge detection algorithm." In 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), edited by Kelin Du and Azlan bin Mohd Zain. SPIE, 2024. http://dx.doi.org/10.1117/12.3038453.

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Shriwas, R. N., Yash Bodkhe, Anushka Mane, and Rahul Kulkarni. "Overview of Canny Edge Detection and Hough Transform for Lane Detection." In 2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0. IEEE, 2024. http://dx.doi.org/10.1109/otcon60325.2024.10688024.

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Zhang, Zhuang, and Yifeng Zhu. "Adaptive Canny edge detection based on fast median filtering." In 5th International Conference on Computer Vision and Data Mining (ICCVDM 2024), edited by Xin Zhang and Minghao Yin. SPIE, 2024. http://dx.doi.org/10.1117/12.3048320.

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Abdullah-Al-Nahid, Yinan Kong, and Md Nazmul Hasan. "Performance analysis of Canny's edge detection method for modified threshold algorithms." In 2015 International Conference on Electrical & Electronic Engineering (ICEEE). IEEE, 2015. http://dx.doi.org/10.1109/ceee.2015.7428227.

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SILVA, G. P., S. A. SANDRI, and A. C. FRERY. "SYNTHETIC APERTURE RADAR EDGE DETECTION WITH CANNY'S PROCEDURE AND A GRAVITATIONAL APPROACH." In The 11th International FLINS Conference (FLINS 2014). WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814619998_0027.

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Vignesh, S. Senthil Pon, and R. M. Bommi. "Determining Average Error of Flank Wear in Turning Duplex Stainless Steel Using Canny's Edge Detection Algorithm in Comparison with Fuzzy Logic Algorithm." In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2023. http://dx.doi.org/10.1109/ic3i59117.2023.10397949.

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Liu, Yang, Lingyu Sun, Lijun Li, Yiben Zhang, Zongmiao Dai, and Zhenkai Xiong. "Image Identification of a Moving Object Based on an Improved Canny Edge Detection Algorithm." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86792.

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Edge detection plays an increasingly critical role in image process community, especially for moving object identification problems. For this case, the target object can be captured straightly via the edges beside which there is an obvious jump of grey value or texture. Nowadays, Canny operator has gained great popularity as it shows higher anti-noise performance and presents better detection accuracy in comparison with other edge detection operators like Robert’s, Sobel’s, Prewitt’s etc. However, the Gaussian filter associated with the classic Canny operator is sometimes too simple to decrease the all-type-noise. Additionally, in order to enhance the detection accuracy and lower the pseudo-edges detection ratio, two thresholds, high and low, are chosen artificially which have actually limited the adaptability of the algorithm. In this work, a compound filter, Gaussian-Median filter, is proposed to improve the smoothing effect. The self-adaptive multi-threshold Otsu algorithm is realized to determine the high/low threshold automatically according to the grey value statistic. Image moment method is conducted on basis of the detected moving object edges to locate the centroid and to compute the principal orientation. The experimental results based upon locating the edges of both static and moving objects proved the good robustness and the excellent accuracy of the proposed method.

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Reports on the topic "Canny's edge detection"

1

Clarke, J., and L. R. Wright. The uncertainty-aware canny operator edge detection method. National Physical Laboratory, 2023. http://dx.doi.org/10.47120/npl.ms49.

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2

Clausen, Jay, Vuong Truong, Sophia Bragdon, et al. Buried-object-detection improvements incorporating environmental phenomenology into signature physics. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45625.

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Abstract:

The ability to detect buried objects is critical for the Army. Therefore, this report summarizes the fourth year of an ongoing study to assess environ-mental phenomenological conditions affecting probability of detection and false alarm rates for buried-object detection using thermal infrared sensors. This study used several different approaches to identify the predominant environmental variables affecting object detection: (1) multilevel statistical modeling, (2) direct image analysis, (3) physics-based thermal modeling, and (4) application of machine learning (ML) techniques. In addition, this study developed an approach using a Canny edge methodology to identify regions of interest potentially harboring a target object. Finally, an ML method was developed to improve automatic target detection and recognition performance by accounting for environmental phenomenological conditions, improving performance by 50% over standard automatic target detection and recognition software.

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