Encoded light image active feature matching approach in binocular stereo vision
Shuang Yu, Chen Baoyuan, Zhao Lei, Xiaoyang Yu, Haibin Wu, Jixun Zhang, Chen Deyun · 2016
Binocular stereo vision is one of the most effective ways to obtain the 3D information of the object, of which the stereo matching is the most important and difficult part. In this paper, we propose an active feature matching approach based on encoded feature patterns, which add active features to the object image through projecting Gray code light to the object. Besides, we set the constraints, propose the searching strategy and take the pixel region code value as the match unit to achieve rough matching. Focused on the problem that several pixels share the same region code value, we set the sliding window and implement precise matching according to the similarity measurement function. Furthermore, we establish the experimental system and carry out experiments on multiple objects. Experimental results show that the proposed approach is feasible and under the same condition, the measurement accuracy of the proposed approach is high than that of the Gray code structured light approach.