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Visual navigation of autonomous vehicles Theory

Author: ZhangLei
Tutor: MaJian
School: Chang'an University
Course: Vehicle Engineering
Keywords: Autonomous vehicles Edge Detection Lane detection Moving Target Detection Computer Vision
CLC: U463.6
Type: Master's thesis
Year: 2005
Downloads: 316
Quote: 1
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Abstract


In this paper, autonomous vehicles visual navigation lane detection and motion detection of these two key technologies are studied. The main contents of the article including image preprocessing - edge detection, lane detection and motion detection . Correctly detect the edges of the image is to achieve one of the key steps lane detection . This paper presents a contour -based multi-scale edge detection algorithm structural elements , in a large noise , you can detect a very good edge of the image , to retain more detail, simulation results show that the method is superior to other methods and classical mathematical morphology edge detection method . In the lane detection in this paper puts forward a road edge detection and color-based image segmentation combining lane detection algorithm can effectively remove the shadows, noise impact point on the lane detection , and can easily be applied to autonomous vehicles visual navigation . Simulation results show that the method in different road conditions can be obtained very good results. Moving target detection in this paper, a new algorithm based on background subtraction , the algorithm using the Gaussian model and the combination of the least square method reduces the prospects for moving tectonic influence Simulation results show that the effect is better than traditional methods.

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CLC: > Transportation > Road transport > Automotive Engineering > Automotive structural components > Electrical equipment and accessories
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