Three-Dimensional Knee Joint Registration Based on Principal Component Analysis and Iterative Closest Point

doi:10.13190/j.jbupt.2019-165

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (3): 112-117.doi: 10.13190/j.jbupt.2019-165

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Three-Dimensional Knee Joint Registration Based on Principal Component Analysis and Iterative Closest Point

WANG Xiao-yu, CHEN Lin

School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China

Received:2019-08-13 Online:2020-06-28 Published:2020-06-24
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Abstract

Abstract: In view of inconsistency between knee joint and prosthesis in spatial coordinate system, a three-stage registration method based on principal component analysis (PCA) and iterative closest point (ICP) algorithm is proposed, which adopts PCA and ICP twice. Firstly, the point cloud data of knee joint and joint prosthesis is registered by PCA. then ICP algorithm is used to adjust the initial registration results. Finally, ICP registration is carried out again for the adjusted point cloud data, so as to adjust its spatial coordinate axis to be consistent. Experiments show that compared with other algorithms, the three-stage registration method can keep high registration accuracy and shorten the registration time.

Key words: opint cloud registration, iterative closest point, principal component analysis, knee joint

CLC Number:

TN911.22

WANG Xiao-yu, CHEN Lin. Three-Dimensional Knee Joint Registration Based on Principal Component Analysis and Iterative Closest Point[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(3): 112-117.

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Three-Dimensional Knee Joint Registration Based on Principal Component Analysis and Iterative Closest Point

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