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Warning system to keep the vehicle in the lane
Fendrich, Vítězslav ; Říha, Kamil (referee) ; Poměnková, Jitka (advisor)
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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Traffic monitoring using Raspberry PI
Zacpal, Michal ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This thesis describes the design and subsequent implementation of a unit for traffic monitoring using Raspberry PI. First section provides a quick overview of assistance systems, which use a road lane detection techniques. Next there is a description of two diferent methods for road lane detection. Follow the description of monitoring scene. Then the work describe the practical part including the design and realization of supporting electronics, selecting of each components, including the modifying of cameras, mechanical design and creating of unit. Another section is about selection and installation of appropriate software components necessary for running of the unit and the selection of development tools for creating user application. After description of graphical user interafce, there is a description of road lanes detection algorithm. At the end of the thesis is summarized a reliability of unit in real traffic situation. At the appendix there are technical drawings, describing the unit.
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Image based road surface segmentation with lane detection
Turoň, Rudolf ; Honec, Peter (referee) ; Zemčík, Tomáš (advisor)
This bachelor thesis deals with road semantic segmentation with lane lines detection. The aim of the thesis is to conduct a survey of methods used for general segmentation and lane lines detection, collect a representative dataset for testing, design a data processing system including implementation for semantic segmentation and detection of lanes in image, video and live camera input. In preprocessing phase images are filtered using morphological transformations. The segmentation is performed using the watershed method with labels, and an adaptive algorithm is designed to find the labels. The lanes are searched for in the thresholded projectively transformed image using the sliding window technique. As a result, a segmentation accuracy of 88.3% is achieved based on the IoU metric. The thesis concludes with a discussion of the obtained results and summarizes the possibilities for further improvements of the system.
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Autonomous control of the vehicle through image processing
Fronc, Leoš ; Píštěk, Václav (referee) ; Kučera, Pavel (advisor)
This diploma thesis deals with the topic of autonomous vehicles and especially lane detection. The paper describes and compares two main approaches to the lane detection - using traditional methods of computer vision and convolutional neural networks. The aim of the work was to create a system that would be able to recognize road lanes in a real time. The proposed system consisted of a Jetson Nano computer, a ZED stereo camera and a programmed algorithm. In total, two algorithms have been developed that use completely different approaches. Finally, the whole system was tested in terms of functionality and lane recognition.
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Autonomous control of the vehicle through image processing
Fronc, Leoš ; Píštěk, Václav (referee) ; Kučera, Pavel (advisor)
This diploma thesis deals with the topic of autonomous vehicles and especially lane detection. The paper describes and compares two main approaches to the lane detection - using traditional methods of computer vision and convolutional neural networks. The aim of the work was to create a system that would be able to recognize road lanes in a real time. The proposed system consisted of a Jetson Nano computer, a ZED stereo camera and a programmed algorithm. In total, two algorithms have been developed that use completely different approaches. Finally, the whole system was tested in terms of functionality and lane recognition.
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Image based road surface segmentation with lane detection
Turoň, Rudolf ; Honec, Peter (referee) ; Zemčík, Tomáš (advisor)
This bachelor thesis deals with road semantic segmentation with lane lines detection. The aim of the thesis is to conduct a survey of methods used for general segmentation and lane lines detection, collect a representative dataset for testing, design a data processing system including implementation for semantic segmentation and detection of lanes in image, video and live camera input. In preprocessing phase images are filtered using morphological transformations. The segmentation is performed using the watershed method with labels, and an adaptive algorithm is designed to find the labels. The lanes are searched for in the thresholded projectively transformed image using the sliding window technique. As a result, a segmentation accuracy of 88.3% is achieved based on the IoU metric. The thesis concludes with a discussion of the obtained results and summarizes the possibilities for further improvements of the system.
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Warning system to keep the vehicle in the lane
Fendrich, Vítězslav ; Říha, Kamil (referee) ; Poměnková, Jitka (advisor)
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.
|
|
|
Traffic monitoring using Raspberry PI
Zacpal, Michal ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This thesis describes the design and subsequent implementation of a unit for traffic monitoring using Raspberry PI. First section provides a quick overview of assistance systems, which use a road lane detection techniques. Next there is a description of two diferent methods for road lane detection. Follow the description of monitoring scene. Then the work describe the practical part including the design and realization of supporting electronics, selecting of each components, including the modifying of cameras, mechanical design and creating of unit. Another section is about selection and installation of appropriate software components necessary for running of the unit and the selection of development tools for creating user application. After description of graphical user interafce, there is a description of road lanes detection algorithm. At the end of the thesis is summarized a reliability of unit in real traffic situation. At the appendix there are technical drawings, describing the unit.
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