基于控制点和RGB向量差联合梯度Census变换的立体匹配算法

doi:10.16451/j.cnki.issn1003-6059.202201004

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Abstract Aiming at the low matching precision of weak texture region and boundary in traditional stereo matching algorithms, a stereo matching algorithm based on control points, RGB vector difference and gradient census transform is proposed. Firstly, a row matching algorithm based on dynamic time warping(DTW) is exploited to find the optimal matching path. The path is distorted and aligned to select matching control points. Then, RGB vector difference cost is combined with gradient Census transform cost as the matching cost of non-control points. The robustness of pixels is enhanced by gradient Census transform, and the three-dimensional color information of the image is retained by the RGB vector. Thus the higher matching precision is achieved. The combination of the matching cost of control points and non-control points is regarded as the initial matching cost. The RGB vector difference is utilized to acquire the adaptive window of different texture areas. The cost aggregation is calculated by the algorithm in a horizontal and vertical directions of an adaptive window. The cost aggregation is employed to optimize the initial cost. Multi-step optimization is employed to reduce the disparity error rate.Finally, the proposed algorithm is validated on Middlebury dataset for different regions and the disparity is calculated in the real scene of robot. The calculated disparity is verified for three-dimensional reconstruction based on the principle of 3D imaging. Both theoretical analysis and experimental results show that the proposed algorithm reduces the matching error rate of weak texture region and boundary significantly.

Key words： Control Points Dynamic Time Warping(DTW) Gradient Census Transform Stereo Matching

Received: 07 June 2021

Fund:National Natural Science Foundation of China(No.61771146)

Corresponding Authors: WEI Hui, Ph.D., professor. His research interests include cognitive science and artificial intelligence.

About author:: WANG Sen, master student. Her research interests include stereo vision.
MENG Lingjiang, Ph.D. candidate. His research interests include stereo vision.

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Cite this article:

WANG Sen,WEI Hui,MENG Lingjiang. Stereo Matching Algorithm Based on Control Points, RGB Vector Difference and Gradient Census Transform[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(1): 37-50.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202201004 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I1/37

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