Thematische Bibliographien / Dopravní značky

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  1. Dissertationen
  2. Bücher

Auswahl der wissenschaftlichen Literatur zum Thema „Dopravní značky“

Autor: Grafiati
Veröffentlicht am 4. Juni 2021
Zuletzt aktualisiert am 17. Februar 2022

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Dissertationen zum Thema "Dopravní značky"

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Solnický, Vojtěch. „Detekce a rozpoznání omezení rychlosti z dopravních značek“. Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-232045.

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This master‘s thesis describes the design and implementation of the system for detection and recognition of speed limit road signs. It focuses on the recognition of the red circular speed limit sign from the image data using the computer vision methods. Several methods were programmed and tested as a part of this thesis. In the final solution, the segmentation based on YCbCr color model is used. Detection of the circular sign and final classification is performed by template matching method. Algorithm for the tracking of the detected signs between frames of the video is used for better performance in real-time recognition. Application is developed using MATLAB and Simulink. The result is a simple driver assistance system prototype, which can be implemented in any computer with camera. The correct function of the algorithm was confirmed during a testing in a traffic.
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Spáčil, Pavel. „Detekce a rozpoznání dopravních značek v obraze“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237057.

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This work focuses on classification and recognition of traffic signs in image. It describes briefly some used methods a deeply describes chosen system including extensions and method for creating models needed for classification. There's described implementation of library and demonstration program including important pieces of knowledge discovered during development. There're also results of some experiments and possible enhancements in conclusion.
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Svoboda, Tomáš. „Detekce, lokalizace a rozpoznání dopravních značek“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236958.

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This master's thesis deals with the localization, detection and recognition of traffic signs. The possibilities of selection of areas with possible traffic signs occurrence are analysed. The properties of different kinds of features used for traffic signs recognition are described next. It focuses on the features based on histogram of oriented gradients. Some possible classifiers are discussed, in the first place the cascade of support vector machines, which are used in resulting system. A description of the system implementation and data sets for 5 types of traffic signs is part of this thesis. Many experiments were accomplished with created system. The results of the experiments are very good. New datasets were acquired from approximately 9 hours of processed video sequences. There are about 13 500 images in these datasets.
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Černá, Tereza. „Detekce a rozpoznání registrační značky vozidla pro analýzu dopravy“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234966.

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This thesis describes the design and development of a system for detection and recognition of license plates. The work is divided into three basic parts: licence plates detection, finding of character positions and optical character recognition. To fullfill the goal of this work, a new dataset was taken. It contains 2814 license plates used for training classifiers and 2620 plates to evaluate the success rate of the system. Cascade Classifier was used to train detector of licence plates, which has success rate up to 97.8 %. After that, pozitions of individual characters were searched in detected pozitions of licence plates. If there was no character found, detected pozition was not the licence plate. Success rate of licence plates detection with all the characters found is up to 88.5 %. Character recognition is performed by SVM classifier. The system detects successfully with no errors up to 97.7 % of all licence plates.
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Oškera, Jan. „Detekce dopravních značek a semaforů“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-432850.

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The thesis focuses on modern methods of traffic sign detection and traffic lights detection directly in traffic and with use of back analysis. The main subject is convolutional neural networks (CNN). The solution is using convolutional neural networks of YOLO type. The main goal of this thesis is to achieve the greatest possible optimization of speed and accuracy of models. Examines suitable datasets. A number of datasets are used for training and testing. These are composed of real and synthetic data sets. For training and testing, the data were preprocessed using the Yolo mark tool. The training of the model was carried out at a computer center belonging to the virtual organization MetaCentrum VO. Due to the quantifiable evaluation of the detector quality, a program was created statistically and graphically showing its success with use of ROC curve and evaluation protocol COCO. In this thesis I created a model that achieved a success average rate of up to 81 %. The thesis shows the best choice of threshold across versions, sizes and IoU. Extension for mobile phones in TensorFlow Lite and Flutter have also been created.
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Číp, Pavel. „Detekce a rozpoznávání dopravních značek“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217772.

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The thesis deals with traffic sign detection and recongnition in the urban environment and outside the town. A precondition for implementation of the system is built-in camera, usually in a car rear-view mirror. The camera scans the scene before the vehicle. The image data are transfered to the connected PC, where the data are transformation to information and evalutations. If the sign was detected the system is visually warned the driver. For a successful goal is divided into four separate blocks. The first part is the preparing of the image data. There are color segmentation with knowledge of color combination traffic signs in Czech Republic. Second part is deals with shape detection in segmentation image. Part number three is deals with recognition of inner pictogram and its finding in the image database. The final part is the visual output of displaying founded traffic signs. The thesis has been prepader so as to ensure detection of all relevant traffic signs in three basic color combinations according to existing by Decree of Ministry of Transport of Czech Republic. The result is the source code for the program MATLAB. .
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Zámečník, Dušan. „Rozpoznání dopravních značek využitím neuronové sítě“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217876.

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This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.
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Šmíd, Josef. „Návrh detektoru dopravních značek pomocí metod zpracování obrazu“. Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417772.

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This master thesis deals with the design of a traffic sign detector using the image processing methods. The OpenCV library for working with images in programming language Python is used for this. The first part reports on the using methods. In the next part, these methods were tested on images of traffic signs taken in traffic in different lighting conditions. The results of these tests led to the design of optimal methods and their settings, which were re-verified by verifying on video of driving in traffic. This also revealed the conditions under which they can operate in real-time systems. Finally, an optimization algorithm for compensation of detection errors was proposed from the monitoring of detection waveforms.
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Špaňhel, Jakub. „Re-identifikace vozidla pomocí rozpoznání jeho registrační značky“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-264932.

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This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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Tlačbabová, Jana. „Obvyklá doba pozorování prvků dopravního značení řidičem“. Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-233166.

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The thesis deals with usual time and frequency of road traffic signs observation by the driver. In the first part is a literature research, there is described the measuring device called eyetracker, that is used to record the eye movement. Furthermore there are kinds of eyetrackers that are currently used. There is also described traffic signs form 1961 until 2009. The second part draws of the video records from driving tests, which were conducted in the towards of this thesis. The results were processed and evaluated data were determinated to find the usual time of observation of traffic signs of drivers and their comparison with the time devoted to driving.
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Bücher zum Thema "Dopravní značky"

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vnútra, Slovakia Ministerstvo. Pravidlá cestnej premávky: A d̕alšie súvisiace predpisy : dopravné značky, podmienky prevádzky vozidiel, dopravné situácie, testy. Bratislava: Gora, 1995.

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Slovakia. Pravidla cestnej premavky: A dalsie suvisiace predpisy: Dopravne znacky, podmienky prevadzky vozidiel, dopravne situacie, testy. Gora, 1995.

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