New color road segmentation method

Ke Liu; Yanxing Liu; Jingyu Yang; Yong-Qing Cheng; Nian-Chun Gu

doi:10.1117/12.135189

14 February 1992 New color road segmentation method

Ke Liu, Yanxing Liu, Jingyu Yang, Yong-Qing Cheng, Nian-Chun Gu

Proceedings Volume 1613, Mobile Robots VI; (1992) https://doi.org/10.1117/12.135189
Event: Robotics '91, 1991, Boston, MA, United States

Abstract

Road segmentation is the critical step in a vision system for outdoor road following. This paper presents a new method for color road segmentation. The basic idea of the method is as follows: each pixel of a color image consists of red, green, and blue intensity values; it can be considered as a feature vector in 3-D RGB space, and the road segmentation can be translated into a statistic classification problem. First, a color normalization transform is used to erase the shadows in a color image; then, the optimal discriminant plane technique is used for feature decorrelation; finally, road segmentation is completed by a minimum distance classifier designed on the optimal discriminant plane. We have done a lot of experiments, and the results show that the present method is effective.

Citation Download Citation

Ke Liu, Yanxing Liu, Jingyu Yang, Yong-Qing Cheng, and Nian-Chun Gu "New color road segmentation method", Proc. SPIE 1613, Mobile Robots VI, (14 February 1992); https://doi.org/10.1117/12.135189

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