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Analysis of 3D Textures Based on Features Extraction

Authors: Samah Yahia; Yassine Ben Salem; Mohamed Naceur Abdelkrim;

Analysis of 3D Textures Based on Features Extraction

Abstract

This paper details an efficient method for the analysis of textures in the 3-dimensional space. The Local Binary Patterns (LBP) and the Grey Level Co-occurrence Matrix (GLCM) which are successfully used in various applications and the Decimal Descriptor Patterns (DDP) which is a new promising method are compared. The performance of these approaches is tested with a large number of 3D textures and evaluated in front of illumination variations, surface and texture rotations. Test of classification are performed over two 3D databases with the multiclass Support Vector Machines (SVM) classifier. Using the DDP method, excellent experimental results are obtained.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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