Abstract:

reo matching in texture and depth discontinuities, a stereo matching algorithm based on multi-feature fusion and tree structure aggregation was proposed. The first step was color image fusion, gradient image Census transform and cost calculation. Next came the matching cost aggregation in the minimum spanning tree generated by the original image. Then the accuracy of stereo matching was further improved through using multi direction scanning line optimization. Finally, through using the left and right consistency check, error matching points were marked and parallax correction is made. In order to verify the effectiveness of the proposed algorithm, and the first set of test images provided were tested using the Middlebury test, and the average error rate is 6.38%; then on both actual scene images error rate testing for depth information extracted was conducted, and the test scenarios point to error rates at 5.76% and 5.55% respectively, demonstrating the practicality of the algorithm.

Key words: stereo matching, multi-feature fusion, minimum spanning tree