JOURNAL ARTICLE

3D Segmentation by Spectral Clustering Using Shape Index

Abstract

3D Segmentation by Spectral Clustering Using Shape Index Rajaallah, E.; Herouane, O.; Moumoun, L.; Gadi, T. Abstract The 3D segmentation is a required pretreatment for many applications of 3D processing objects (Search by content, compression, animation, etc…). The design of a segmentation algorithm must take into account the purpose of the algorithm and the application domain to which it is intended. We propose in this paper a new approach to construct the recursive spectral clustering technique using a similarity matrix. This approach is based on the shape index values of adjacent faces and a hierarchical segmentation by optimal recursive cuts. The experimental results obtained are very encouraging and have allowed us to evidence the effectiveness of our approach for segmentation of 3D objects. Full Text: PDF DOI: 10.15640/jcsit.v2n3-4a2

Keywords:
Segmentation Spectral clustering Cluster analysis Computer science Artificial intelligence Scale-space segmentation Segmentation-based object categorization Similarity (geometry) Pattern recognition (psychology) Construct (python library) Image segmentation Animation Index (typography) Computer vision Image (mathematics) Computer graphics (images)

Metrics

2
Cited By
0.48
FWCI (Field Weighted Citation Impact)
0
Refs
0.73
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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