Abstract: As the high error matching rates of the traditional pixel-based matching algorithm, a stereo matching algorithm based on image region segmentation and Belief Propagation(BP) is proposed. The mean shift algorithm is applied to segment the reference image into regions with homogeneous color, and the initial disparity of each pixel is calculated by means of the adaptive weights approaches. The disparity plane parameters are collected by plane model fitting on each segmented region. The ultimate disparity map is acquired by calculated the regional optimal disparity plane, which uses the improved region-based belief propagation algorithm. Compared with the pixel-based global optimization algorithms such as classical BP and Graph Cut(GC) algorithm, this algorithm can greatly reduce the error matching rates especially in textureless regions and occluded regions.
image region segmentation,