Shape similarity measurement for 3D mechanical part using D2 shape distribution and negative feature decomposition

Authors:
Han-Chung Cheng;Cheng-Hung Lo;Chih-Hsing Chu;Yong Se Kim
Affiliations:
Department of Industrial Engineering and Engineering Management, University of National Tsing Hua University, Hsinchu 30013, Taiwan;Department of Industrial Engineering and Engineering Management, University of National Tsing Hua University, Hsinchu 30013, Taiwan;Department of Industrial Engineering and Engineering Management, University of National Tsing Hua University, Hsinchu 30013, Taiwan;School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
Venue:
Computers in Industry
Year:
2011

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Abstract

This paper proposes a novel measurement scheme of 3D shape similarity that integrates D2 Shape Descriptor and Negative Feature Decomposition (NFD). Using NFD, the scheme firstly converts a 3D mechanical part into a tree structure of geometrical primitives decomposed from the part model, namely Negative Feature Tree (NFT). The D2 shape descriptions of these primitives are then produced for further similarity assessments. We assess the shape similarity on a level-by-level basis between the NFTs of a query part and a candidate part. The weighted sum of the similarity values computed on each level is then used as a measure of the overall similarity between the two parts. Our approach combines the simplicity of D2 shape description while overcoming its insensitivity to negative features with NFD. It performs more consistently than the method of Convex Hull Difference (CHD). A comparison with the assessment results using D2 and CHD demonstrates the effectiveness of the new scheme.