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JOIG 2022 Vol.10(1): 1-9
doi: 10.18178/joig.10.1.1-9

An Adaptive Differential Evolution Algorithm with a Point-Based Approach for 3D Point Cloud Registration

Linh Tao 1, Trung Nguyen 1, Tinh Nguyen 1, Toshio Ito 2, and Tam Bui 1,2
1. School of Mechanical Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam
2. Department of Machinery and Control Systems, Shibaura Institute of Technology, Japan

Abstract—This paper presents a novel pairwise registration approach, which aligns images of the same object that have different ranges. By using a point search medium instead of a conventional six-dimensional parameter to reduce the number of search dimensions, the new method resulted in a higher convergence rate and robustness in the same search conditions. The approach integrated a hybrid registration strategy, a combination of Iterative Closest Point (ICP) as a local aligning tool and a global search algorithm such as simulated annealing, particle swarm optimization, differential evolution, etc. An adaptive differential evolution algorithm called ISADE was chosen as the best-so-far global search algorithm. Different experiments on different datasets were carried out. In the new method, as compared with the conventional approach, better aligning results in convergence rate and robustness were observed.

Index Terms—hybrid registration, 3D registration, ICP, global optimization algorithm, point-based registration

Cite: Linh Tao, Trung Nguyen, Tinh Nguyen, Toshio Ito, and Tam Bui, "An Adaptive Differential Evolution Algorithm with a Point-Based Approach for 3D Point Cloud Registration," Journal of Image and Graphics, Vol. 10, No. 1, pp. 1-9, March 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.