Addressing the low matching accuracy of existing stereo matching algorithms in weak texture and depth discontinuous regions, a stereo matching algorithm based on adaptive region division is proposed. First, the cross domain algorithm is used to obtain the arm length of a pixel and calculate the pixel change rate to complete the region division. Then, the absolute difference algorithm, the improved Census transform, and the adaptive weighted gradient operator are used to calculate the initial cost volume which is aggregated by cross domain. The aggregated images are optimized by the improved guidance map filtering and the winner take all strategy is used to filter the optimal disparity. Finally, the final disparity map is obtained by using left and right consistency detection, iterative region voting, disparity filling optimization, and median filtering. The test results based on the Middlebury test platform show that the average error rate of the proposed algorithm is 4.21%, which is an effective matching accuracy improvement in terms of the weak texture and depth-discontinuous regions.