Stereo Image Matching Algorithm Based on Texture Segmentation and Color Segmentation
Chao Li, Yongxing Jia, Huali Wang, Chuanzhen Rong, Ying Zhu · 2020
The traditional binocular vision stereo matching replaces and responds to the maximum point as the feature point, which is prone to uneven distribution of feature points, especially when the distribution of image texture strength is large. The Euclidean distance needs to be calculated when the feature points are matched, and the constraints considered are basically position relationships, ignoring the color block constraints. Based on the image texture and color distribution characteristics, the texture strength area and RGB color block are respectively calculated, and the image is segmented. The multi threshold feature points detection is used, and the matching points are calculated according to the color segmentation template. The experimental results show that compared with the traditional ORB algorithm, the proposed algorithm improves the uniformity of feature points and the matching accuracy.