Road Segmentation Based on Learning Classification
作者单位：College of Mechatronical Engineering and Automation National University of Defense Technology
会议名称：《2010 3rd International Conference on Computer and Electrical Engineering(ICCEE 2010)》
会议日期：2012年
学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
基 金：supported by NSFC(Grant No.90820302,No.90820015) supported by Hunan Provincial Innovation Foundation for Postgraduate
关 键 词：Monocular vision image segment super pixel road detection
摘 要：In vision navigation tasks, the road segmentation is a useful method. Usually, roads can be detected using image segmentation and related image process methods. However such methods always rely on specific road prior knowledge, and they are difficult to be realized in different environments. In this paper the learning classification is proposed. In the learning process the roads of different environments are labeled and learned. In the classification process the road is segmented and selected. Experiments results show that even the roads change the correct results could be got for online process.