This paper proposes a de-occlusion stereo matching algorithm using regional prior information. According to this algorithm, the reference image is segmented using edge detection and region growing. The homogeneous regions after segmentation are regarded as the regional prior information and introduced into the cost calculation for weakening the sensitivity of the cost function to occlusion regions. Area consistency detection is used for correcting occlusions and mismatched pixels to obtain an accurate disparity map. The proposed algorithm is an additive algorithm that can effectively improve the matching effect of the original algorithm when applied to occlusion areas without significantly increasing the amount of calculation. The result of testing the proposed algorithm on the Middlebury dataset proves that the algorithm can effectively reduce the mismatching rate when analyzing occlusion regions.