Lane line recognition for driverless vehicles based on Hough transform

Ma Jin; Pengyu Sun; Xiaolong Li; Kerui Xia; Yiqun Liu; Shu Zhang; Pinjia Zhang

doi:10.1117/12.2640218

1 August 2022 Lane line recognition for driverless vehicles based on Hough transform

Ma Jin, Pengyu Sun, Xiaolong Li, Kerui Xia, Yiqun Liu, Shu Zhang, Pinjia Zhang

Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 122570W (2022) https://doi.org/10.1117/12.2640218
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China

Abstract

Image processing is a key link in the process of automobile intelligence. Image pretreatment methods are studied, including gray processing, binarization and extraction of regions of interest. Three different methods of gray image are compared, and the maximum interclass variance method is used for binarization processing of images. When the image is too bright or too dark, the recognition is very inaccurate. Then the edge detection and straight line acquisition were studied to identify the lane lines, and the Canny edge detection was studied, including Gaussian filtering smoothing, Sobel operator, non-maximum suppression and double threshold edge extraction, and the Canny algorithm was improved and optimized to study the Hough transform. Hough transform is used to extract the straight lines to recognize the lane lines.

Citation Download Citation

Ma Jin, Pengyu Sun, Xiaolong Li, Kerui Xia, Yiqun Liu, Shu Zhang, and Pinjia Zhang "Lane line recognition for driverless vehicles based on Hough transform", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 122570W (1 August 2022); https://doi.org/10.1117/12.2640218

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