Multi-scale Color Local Binary Patterns for Visual Object Classes Recognition

Chao Zhu 1 Charles-Edmond Bichot 1 Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : The Local Binary Pattern (LBP) operator is a computationally efficient yet powerful feature for analyzing local texture structures. While the LBP operator has been successfully applied to tasks as diverse as texture classification, texture segmentation, face recognition and facial expression recognition, etc., it has been rarely used in the domain of Visual Object Classes recognition mainly due to its deficiency of power for dealing with various changes in lighting and viewing conditions in real-world scenes. In this paper, we propose six novel multi-scale color LBP operators in order to increase photometric invariance property and discriminative power of the original LBP operator. The experimental results on the PASCAL VOC 2007 image benchmark show significant accuracy improvement by the proposed operators as compared with both the original LBP and other popular texture descriptors such as Gabor filter.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01381600
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Submitted on : Friday, October 14, 2016 - 2:49:59 PM
Last modification on : Monday, December 10, 2018 - 5:55:13 PM

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Chao Zhu, Charles-Edmond Bichot, Liming Chen. Multi-scale Color Local Binary Patterns for Visual Object Classes Recognition. International Conference on Pattern Recognition (ICPR), Aug 2010, Istanbul, Turkey. pp.3065-3068, ⟨10.1109/ICPR.2010.751⟩. ⟨hal-01381600⟩

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