Performance Evaluation of Face Recognition using LBP, PCA and SVM

International Journal of Computer Science and Engineering

© 2016 by SSRG - IJCSE Journal

Volume 3 Issue 4

Year of Publication : 2016

Authors : Bhumika Pathya, Sumita Nainan

10.14445/23488387/IJCSE-V3I4P118

How to Cite?

Bhumika Pathya, Sumita Nainan, "Performance Evaluation of Face Recognition using LBP, PCA and SVM," SSRG International Journal of Computer Science and Engineering , vol. 3,  no. 4, pp. 58-61, 2016. Crossref, https://doi.org/10.14445/23488387/IJCSE-V3I4P118

Abstract:

Face recognition is the simplest person identification method. Face has been has been chosen as modality for person identification owning to its simplicity in implementation as well as being a noninvasive method in achieving results. Besides its popularity, face recognition still faces issues on its accuracy. It has been observed that while using principal component analysis on varying ambient illumination, recognition accuracy reduces whereas using local binary pattern gives 100% accuracy. For classification, support vector machine is adopted as classifier. The system utilises Yaledatabase and ORL database for experimental results.

Keywords:

Face Recognition, Local Binary Pattern, Support Vector Machine, Principal Component Analysis.

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