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Proceedings Paper

A stereo matching handling model in low-texture region
Author(s): Yi Ma; Yi Zhang; Jin Han; Lianfa Bai
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Paper Abstract

In binocular stereo matching, mistakes are relatively easy to appear in low-texture region due to the weak detail information. In order to eliminate the matching ambiguity as well as guarantee the matching rate, this paper proposes a stereo matching algorithm based on image segmentation. In most low-texture region, traditional cost functions are usually used, and the algorithm can only ameliorated through methods such as reasonable support window, dynamic programming and so on. The results of these algorithms make the whole image smooth, and lose many details. The matching cost function in our algorithm is based on the assumption that pixels are similar in homogeneous area, and reduce the use of multiplication so as to obtain better visual effects and decrease the computational complexity. The first is forming the segmentation maps of stereoscopic images as the guidance. Next comes calculating the aggregation cost in stereo matching in both horizontal and vertical direction successively referring to the segmentation maps. Eventually achieving the final disparity map with optimization algorithm, using WTA(Winner-Takes-All) as principle. The computational complexity of this algorithm is independent of the window size, and suitable for different sizes and shapes. The results of experimental show that this algorithm can get better matching precision about the colorful low-texture stereo image pairs, with few increase in computational complexity. This algorithm, to some extent, can improve the match quality of the regions with repeat texture.

Paper Details

Date Published: 15 October 2015
PDF: 6 pages
Proc. SPIE 9674, AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology, 967439 (15 October 2015); doi: 10.1117/12.2205134
Show Author Affiliations
Yi Ma, Nanjing Univ. of Science and Technology (China)
Yi Zhang, Nanjing Univ. of Science and Technology (China)
Jin Han, Nanjing Univ. of Science and Technology (China)
Lianfa Bai, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9674:
AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology
Haimei Gong; Nanjian Wu; Yang Ni; Weibiao Chen; Jin Lu, Editor(s)

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