文献类型：会议论文

英文题名：A fast road image segmentation algorithm based on cellular neural networks

作者：Xu Guobao[1,2];Yin Yixin[1];Yin Lu[1];Hao Yanshuang[1];Zhou Meijuan[2]

机构：[1]Univ Sci & Technol Beijing, Sch Informat Engn, Beijing 100083, Peoples R China;[2]Guangdong Ocean Univ, Informat Sch, Zhanjiang 524088, Peoples R China

会议论文集：26th Chinese Control Conference

会议日期：JUL 26-31, 2007

会议地点：Zhangjiajie, PEOPLES R CHINA

语种：英文

外文关键词：cellular neural networks; road detection; image segmentation; vision navigation

外文摘要：The main factors that affect segmentation of unstructured road images are shadows and water marks on the road surface. Taking advantage of the parallel image processing capability of cellular neural networks, a fast algorithm for road image segmentation based on cellular neural networks was proposed. In the algorithm, gray threshold segmentation, dilation and erosion, and edge detection using CNN are performed successively. Experimental results demonstrated that the algorithm has strong environmental adaptability, which can fast segment structured and unstructured roads. The proposed method can segment the lane area quickly, effectively and robustly, and can eliminate the influence of shadows and water marks on the segmentation of road images.