针对目前双目视觉立体匹配算法计算量过大、实时性不强的问题, 提出了一种平行配置系统的快速立体匹配算法。利用两幅视图的差异将视图分为特征点和非特征点, 然后对特征点采用WTA (winner-take-all)方法进行匹配, 而对非特征点只进行简单的验证, 最后得出致密的视差图。该算法利用视差的分段连续性, 大大减少了运算量。实验结果表明, 该算法提取的特征点集中于视差不连续区, 与目前其它基于区域的匹配算法相比, 该算法得到的误匹配像素百分比与其它算法相当, 而计算速度却提高了一个数量级, 并且边缘特征较好, 是一种有效可行的高实时性立体匹配算法。

To resolve the problem of large computational cost and bad real-time performance of current binocular vision stereo matching algorithm, a fast stereo matching algorithm of parallel system is presented. Firstly, based on the difference oftwo images, the images are divided into feature points and non-feature points. Then the feature points are matched using winner-take-all (WTA) method and the non-feature points are validated simply. Finally a dense disparity map is yielded. With the fact that the disparity map consists of piecewise-smooth surfaces, the computational cost is decreased greatly. Experimental results show that the extracted feature points are concentrated in the depth discontinuity regions. Compared with other area-base matching algorithms, the computational speed of the presented algorithm has been improved for one order of magnitude while the percentage of bad matching pixels is equivalent to other algorithms. Besides, the edge feature is better, and thus this method is an effective and feasible stereo matching algorithm with good real-time performance.