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Mathematical Problems in Engineering
Volume 2015, Article ID 137193, 8 pages
Research Article

Stereo Matching Algorithm Based on 2D Delaunay Triangulation

State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China

Received 5 January 2015; Accepted 26 May 2015

Academic Editor: Simon X. Yang

Copyright © 2015 Xue-he Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


To fulfill the applications on robot vision, the commonly used stereo matching method for depth estimation is supposed to be efficient in terms of running speed and disparity accuracy. Based on this requirement, Delaunay-based stereo matching method is proposed to achieve the aforementioned standards in this paper. First, a Canny edge operator is used to detect the edge points of an image as supporting points. Those points are then processed using a Delaunay triangulation algorithm to divide the whole image into a series of linked triangular facets. A proposed module composed of these facets performs a rude estimation of image disparity. According to the triangular property of shared vertices, the estimated disparity is then refined to generate the disparity map. The method is tested on Middlebury stereo pairs. The running time of the proposed method is about 1 s and the matching accuracy is 93%. Experimental results show that the proposed method improves both running speed and disparity accuracy, which forms a steady foundation and good application prospect for a robot’s path planning system with stereo camera devices.