Area Based Stereo Image Matching Technique Using Hausdorff Distance and Texture Analysis

A conventional image matching techniques may be classified as either area based or feature based methods. In this paper an area based image matching method is proposed for dense disparity map. The method is a composite technique where first the similarity measure between template window and search window is found by normalized cross correlation technique. Few best matches are selected for the template window from the search sub windows, considering the largest normalized cross correlation coefficient. Further edge map is obtained for stereo image pair using canny edge detector. The matches for the template window are filtered using Hausdorff distance technique. Further texture analysis of the same template window and selected search windows is the third measure to decide the accurate match. Texture analysis is done with the co-occurrence matrices which is a two dimensional histogram of the occurrence of pair of intensity value in a given spatial relationship. With this composite method dense point to point correspondence can be achieved with greater accuracy. This method is tolerant to radiometric distortions and parallel processing of the three techniques will improve the speed.