A Stereo Matching Algorithm Based on Image Segmentation and Features Point

A novel method is presented based on image segmentation and features point for stereo matching. Firstly, we analyse texture of the original image for distinguishing less texture and similar texture regions, as a result, we can achieve image segmentation by label image texture region. Meanwhile, we can remove smaller regions by blob filter; Then, SIFT features point and matching can achieve reliable and sparse disparity; secondly, we can gain primly disparity with SAD area-based matching; Finally, according to distribution of SIFT matching features, disparity continuous constraint and minimum distance classifier, we can be successful to get disparity of image segmentation block. The results of experiment with standard test images show this paper presents a method is effective. Compared with traditional methods, the method can obtain quickly, dense and high precision disparity map.