文献类型：期刊文献

英文题名：A fast edge detection algorithm based on cellular neural networks for road images

作者：Xu, Guobao[1]; Xie, Shiyi[1]; Yin, Yixin[2]; Zhou, Meijuan[1]; Zhang, Shilong[3]

机构：[1] Lab of Ocean Remote Sensing and Information Technology, Guangdong Ocean University, Zhanjiang 524088, Guangdong, China; [2] School of Information Engineering, University of Sci. and Tech. Beijing, Beijing 100083, China; [3] School of Computer Science and Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, Guangdong, China

年份：2012

卷号：7

期号：1

起止页码：426

外文期刊名：International Review on Computers and Software

收录：EI(收录号：20123115300944)、Scopus(收录号：2-s2.0-84864357738)

语种：英文

外文关键词：Salt and pepper noise - Signal detection - Edge detection - Roads and streets - Image enhancement - Mobile robots - Cellular neural networks - Mathematical morphology

外文摘要：Mobile robot road image edge detection plays an important role in improving the accuracy of identification for roads image. Taking into account the real-time requirement for visual navigation of mobile robots, the early visual segmentation method based on mathematical morphology was studied in this work. An edge detection algorithm based on cellular neural networks for processing road images was proposed. The proposed algorithm can eliminate the influence of salt and pepper noises and cracks on the edge detection of road images, segment the road region and extract the road edges quickly and accurately. Therefore, it paves the way for follow-up mobile robot visual navigation. ? 2012 Praise Worthy Prize S.r.l. - All right reserved.