Analysis of Local Descriptors for Human Face Recognition

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 43)

Abstract

Facial image analysis is an important and profound research in the field of computer vision. The prime issue of the face recognition is to develop the robust descriptors that discriminate facial features. In recent years, the local binary pattern (LBP) has attained a big attention of the biometric researchers, for facial image analysis due to its robustness shown for the challenging databases. This paper presents a novel method for facial image representation using local binary pattern, called augmented local binary pattern (A-LBP) which works on the consolidation of the principle of locality of uniform and non-uniform patterns. It replaces the non-uniform patterns with the mod value of the uniform patterns that are consolidated with the neighboring uniform patterns and extract pertinent information from the local descriptors. The experimental results prove the efficacy of the proposed method over LBP on the publicly available face databases, such as AT & T-ORL, extended Yale B, and Yale A.

Keywords

Face recognition Local binary pattern Histogram Descriptor 

Notes

Acknowledgment

The authors acknowledge the Institute of Engineering and Technology (IET), Lucknow, Uttar Pradesh Technical University (UPTU), Lucknow for their financial support to carry out this research under the Technical Education Quality Improvement Programme (TEQIP-II) grant.

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringInstitute of Engineering and TechnologyLucknowIndia

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