An Improved Adaptive Window Stereo Matching Algorithm

Wenbo Qiao, Yuanping Xu, Chaolong Zhang, Zhijie Xu, Jian Huang, Pan Xie, Jun Lu

Research output: Contribution to journalConference articlepeer-review

5 Citations (Scopus)


In order to solve the problem that the existing adaptive window stereo matching algorithms have insufficient feature extraction in low-texture regions, resulting in low matching accuracy. An adaptive window stereo matching algorithm based on the gradient is proposed. Firstly, the Sobel operator is used to extract the gradient value of each pixel in the image. Then, each pixel is divided into high, medium and low texture regions according to the gradient value. Next, different arm length thresholds are assigned to different region pixels, and matching windows are generated dynamically according to arm length and color threshold. Finally, the pixels closer to the center of the window are given higher weights by generating windows several times. It solves the problem that the stereo matching algorithm can not select a matching window dynamically. Experimental results on Middlebury dataset show that the proposed method improves the matching accuracy by 5.5% compared with the latest adaptive window stereo matching algorithm.

Original languageEnglish
Article number012066
Number of pages7
JournalJournal of Physics: Conference Series
Issue number1
Early online date13 Oct 2020
Publication statusPublished - 13 Oct 2020
Event3rd International Conference on Computer Information Science and Application Technology - Dali, China
Duration: 17 Jul 202019 Jul 2020
Conference number: 3


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