Academy & Industry Research Collaboration Center (AIRCC)

Volume 9, Number 3, March 2019

Occlusion Handled Block-Based Stereo Matching with Image Segmentation


Jisu Kim, Cheolhyeong Park, Ju O Kim and Deokwoo Lee, Keimyung University, Republic of Korea


This paper chiefly deals with techniques of stereo vision, particularly focuses on the procedure of stereo matching. In addition, the proposed approach deals with detection of the regions of occlusion. Prior to carrying out stereo matching, image segmentation is conducted in order to achieve precise matching results. In practice, in stereo vision, matching algorithm sometimes suffers from insufficient accuracy if occlusion is inherent with the scene of interest. Searching the matching regions is conducted based on cross correlation and based on finding a region of the minimum mean square error of the difference between the areas of interest defined in matching window. Middlebury dataset is used for experiments, comparison with the existed results, and the proposed algorithm shows better performance than the existed matching algorithms. To evaluate the proposed algorithm, we compare the result of disparity to the existed ones.


Occlusion, Stereo vision, Segmentation, Matching