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Traffic Signs Detection and Recognition
Číp, Pavel ; Honec, Peter (referee) ; Horák, Karel (advisor)
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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Usual time and frequency of road traffic signs observation by the driver
Tlačbabová, Jana ; Sedlák, Robert (referee) ; Bradáč, Albert (advisor)
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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Detection of Traffic Signs in Image and Video
Kočica, Filip ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
This thesis deals with the traffic sign detection problematics using modern techniques in image processing. Special architecture of deep convolutional neural network YOLO, i.e. You Only Look Once, which performs both detection and classification in one step, has been used. This architecture allows object detector to work on very high speeds. This thesis also deals with comparison of models trained on real and synthetic datasets. The best model trained on real dataset has reached 63.4% mAP success rate and 82.3% mAP when trained on synthetic dataset. Evaluation of one image takes about ~40.4ms on average graphics processing unit and ~3.9ms on higher than average graphics processing unit. The benefit of this thesis is that under certain conditions neural network model trained on synthetic data can achieve same or even better results than model trained on real data. This may simplify process of object detector development since it is not necessary to annotate large number of images.
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Cleaning equipment for the road signs
Kuře, Radim ; Škopán, Miroslav (referee) ; Kašpárek, Jaroslav (advisor)
The main aim of this bachelor thesis is to design the construction of cleaning equipment for the road signs. Introductory part of thesis contains tractors which are used in road maintenance and similar equipment in this area. The main part is dedicated to design of cleaning equipment for the road signs.
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Cleaning equipment for the road signs
Kuře, Radim ; Škopán, Miroslav (referee) ; Kašpárek, Jaroslav (advisor)
The main aim of this bachelor thesis is to design the construction of cleaning equipment for the road signs. Introductory part of thesis contains tractors which are used in road maintenance and similar equipment in this area. The main part is dedicated to design of cleaning equipment for the road signs.
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Detection of Traffic Signs in Image and Video
Kočica, Filip ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
This thesis deals with the traffic sign detection problematics using modern techniques in image processing. Special architecture of deep convolutional neural network YOLO, i.e. You Only Look Once, which performs both detection and classification in one step, has been used. This architecture allows object detector to work on very high speeds. This thesis also deals with comparison of models trained on real and synthetic datasets. The best model trained on real dataset has reached 63.4% mAP success rate and 82.3% mAP when trained on synthetic dataset. Evaluation of one image takes about ~40.4ms on average graphics processing unit and ~3.9ms on higher than average graphics processing unit. The benefit of this thesis is that under certain conditions neural network model trained on synthetic data can achieve same or even better results than model trained on real data. This may simplify process of object detector development since it is not necessary to annotate large number of images.
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Traffic sign classification by deep learning
Harmanec, Adam ; Blažek, Jan (advisor) ; Kratochvíl, Miroslav (referee)
Classification of road signs has been studied for many years and very promising results have been achieved. We present the analysis of used data sets as very limited for real case classification. In this thesis we analyse publicly available data sets and by merging and extending them, we create a wider and more comprehensive data set applicable in the Czech Republic. Finally, we propose a new convolutional neural network architecture and test it along with several preprocessing techniques on the new data set reaching accuracy of over 99%.
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Usual time and frequency of road traffic signs observation by the driver
Tlačbabová, Jana ; Sedlák, Robert (referee) ; Bradáč, Albert (advisor)
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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Traffic Signs Detection and Recognition
Číp, Pavel ; Honec, Peter (referee) ; Horák, Karel (advisor)
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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Využití GPU výpočtů pro rozpoznání dopravních značek
Zídek, Karel
The thesis deals with the problem of GPU acceleration of algorithms for traffic sign recognition. Theoretical part of the thesis outlines methods for object detection with emphasis on the traffic sign detection problem. Further, it provides comparison of two well known tools for programming on the GPU: CUDA and OpenCL. On the basis of the review, an architecture of own solution is proposed. Finally, the thesis contains description of the implementation as well as evaluation of the results.
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