For the mismatching problem in computer vision,a fast local stereo matching algorithm based on seed pixel propagation was proposed to further improve the efficiency of matching algorithm.Firstly,the edge of an image was extracted using Canny operator in order to overcome the adverse influence of a fixed window on stereo matching by combining with the edge information to construct a dynamic matching window.Then,the AD-Census combined matching costs was used to realize the cost aggregation on the dynamic window,the initial disparity map was obtained by WTA search strategy and the disparity was filtrated to get seed pixels.Furthermore,the color difference between pixels was used to propagate the disparity of seed pixels to around unseeded pixels.Finally,the region voting and local rectification were adopted to refine the disparity and to get the accuracy dense disparity map.Experimental results show that the algorithm provides high-quality disparity map on Middlebury data set,the computing time is accelerated by 1.8 times as compared with that of newer local matching algorithms at present.It meets the demands of actual applications for accuracy and speeds.