Dense stereo matching by region growing based on disparity space sampling

Abstract

Through the research of the existing region growing method,the authors presented an improved algorithm,which was unlike the existing region growing algorithm that depended on the accuracy of the seeds.The algorithm can continue growing on the smooth region and repetitive patterns region.Firstly,obtain the initial set of seeds in the disparity space by matching the Harris points.Then build the newly growing method in the disparity space.The results demonstrate it can trace out the disparity space.In the growing process,it can rectify the wrong matching automatically,and guarantee matching accuracy and correctness in the smooth and repetitive pattern region.