Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0215008(2021)

Stereo Matching Algorithm Based on Improved Census Transform and Gradient Fusion

Hong Xiao, Chuan Tian*, Yi Zhang, Bo Wei, and Jiaqi Kang
Author Affiliations
  • School of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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    Binocular stereo matching transforms plane vision into three-dimensional stereo vision based on the parallax principle, which is one of the core steps of three-dimensional reconstruction. Aiming at the problems of local stereo matching algorithm in the depth discontinuity, low matching accuracy in weak texture areas, and easy to be interfered by factors such as light and noise, an improved stereo matching algorithm is proposed in this paper. First, in the cost calculation stage, the improved Census cost and the gradient cost are fused, and the guided filtering algorithm is used to perform multi-scale cost aggregation on the image; then, the winner-take-all algorithm is used to calculate the initial disparity; finally, the left-right consistency detection, middle value filtering performs disparity post-processing to obtain the final disparity image. Experimental results show that the average mistake match rate of the algorithm on the Middlebury2.0 test platform is 5.11%, and it has good robustness and practicability.

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    Hong Xiao, Chuan Tian, Yi Zhang, Bo Wei, Jiaqi Kang. Stereo Matching Algorithm Based on Improved Census Transform and Gradient Fusion[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0215008

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    Paper Information

    Category: Machine Vision

    Received: Jul. 1, 2020

    Accepted: Jul. 22, 2020

    Published Online: Jan. 11, 2021

    The Author Email: Tian Chuan (zgtchuan@qq.com)

    DOI:10.3788/LOP202158.0215008

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