提出了一种基于分割的两步立体匹配算法。第1步，利用动态规划和左右一致性约束计算地面控制点，将原始图像分割为许多小区域，假定每一个区域为同一个视差，并通过地面控制点计算部分区域的视差值；第2步将剩余未匹配的区域编码为一条染色体，用遗传算法进行优化，得到最终的稠密视差图。选用了一些标准图像对进行测试，实验结果表明，该算法具有很好的性能。

A segment-based two-step stereo correspondence algorithm is proposed. In the first step, Dynamic Programming and Left-Right Consistency are used to detect ground control points, and the original image is segmented into small areas, where each of them is assumed as a single disparity, mean while the detected GCP are used to compute the disparity value of the part of the image; In the second step, the left unmatched areas are coded as a single chromosome, and are optimized with genetic algorithm to generate the dense stereo disparity map. The algorithm is tested on the standard image pairs, and the experimental results show its good performance.