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  • Received: Dec. 10, 2019

    Accepted: Mar. 9, 2020

    Posted: Oct. 1, 2020

    Published Online: Oct. 17, 2020

    The Author Email: Li Chun (2351583604@qq.com)

    DOI: 10.3788/LOP57.201015

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    Yong Wang, Chun Li. Point Cloud Adaptive Registration Algorithm Based on Color Information and Geometric Information[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201015

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Laser & Optoelectronics Progress, Vol. 57, Issue 20, 201015 (2020)

Point Cloud Adaptive Registration Algorithm Based on Color Information and Geometric Information

Wang Yong1 and Li Chun2,*

Author Affiliations

  • 1Liangjiang College of Artificial Intelligence, Chongqing University of Technology, Chongqing 401135, China
  • 2School of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China

Abstract

In the three-dimensional point cloud registration, when the surface of the point cloud is relatively flat and the geometric features are fuzzy, the iterative closest point algorithm has poor registration results, even often fails to register. The point cloud data obtained by the three-dimensional laser scanner includes geometric coordinate information and RGB information. Here, by making full use of point cloud coordinate information and RGB information, we propose a new point cloud registration method, which first convert RGB values into grayscale values, set the weighting factor according to the sum of the variance of the gray value and the sum of the variances of each curvature, and then adaptively adjust the impact of color information and geometric information on registration in the light of the weighting factor to achieve an organic combination based on color information and geometric information. Experimental results show that the proposed method can achieve stable and accurate registration of different point clouds.

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