关键词: 机器视觉, 双目视觉, 立体匹配算法, 代价聚合, 视差优化

Abstract: To vanquish the problems of low accuracy and mismatching in weak texture region,an Anisotropic Stereo Matching algorithm with Multi-Scale Information(ASMSI)was proposed.An anisotropic matching cost function was constructed,the gradient and phase angle information were introduced into the cost calculation process to eliminate outliers in the weak texture region.Besides,cross-based cost aggregation was adopted to calculate the matching cost value of each support region.Additionally,a winner-take-all strategy was employed to generate the initial disparity map.On this basis,the refined parallax chart was produced by left and right consistency detection and post-processing.Numerical simulations were carried out to compare the mismatching rate,running time of non-occlusion and depth-discontinuous regions of images to evaluate the algorithm model.The simulation results verified that the presented approach solved the mismatching problems of weak texture region effectively and improve the matching accuracy by 5.02%,which could satisfy the requirements of efficacy and high precision in the stereo matching process.

Key words: machine vision, binocular vision, stereo matching algorithm, cost aggregation, disparity optimization