10 July 2009 Vision-based road detection by hidden Markov model
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Proceedings Volume 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering; 74890Y (2009) https://doi.org/10.1117/12.836839
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
A novel vision-based road detection method was proposed in this paper to realize visual guiding navigation for ground mobile vehicles (GMV). The original image captured by single camera was first segmented into the road region and nonroad region by using an adaptive threshold segmentation algorithm named OTSU. Subsequently, the Canny edges extracted in grey images would be filtered in the road region so that the road boundary could be recognized accurately among those disturbances caused by other edges existed in the image. In order to improve the performance of road detection, the dynamics of GMV and the Hidden Markov Model (HMM) was taken into account to associate the possible road boundary at different time step. The method proposed in this paper was robust against strong shadows, surface dilapidation and illumination variations. It has been tested on real GMV and performed well in real road environments.
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Yanqing Wang, Yanqing Wang, Deyun Chen, Deyun Chen, Liyuan Tao, Liyuan Tao, Chaoxia Shi, Chaoxia Shi, "Vision-based road detection by hidden Markov model", Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 74890Y (10 July 2009); doi: 10.1117/12.836839; https://doi.org/10.1117/12.836839
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