Based on Line Matching in Hough Space Using Dynamic Programming

This paper presents a method of using Hough space for solving the correspondence problem in stereo vision. It is shown that the line-matching problem in image space can readily be converted into a point-matching problem in Hough (p-8) space. Dynamic programming can be used for searching the optimal matching, now in Hough space. The combination of multiple constraints, especially the natural embedding of the constraint of figural continuity, ensures the accuracy of the matching. The time complexity for searching in dynamic programming is O(pmn) , where m and n are the numbers of the lines for each 8 in the pair of stereo images, respectively, and p is the number of all possible line orientations. Since m and n are usually fairly small, the matching process is very efficient. Experimental results from both binocular and trinocular matchings are presented and analyzed.