On projection-based methods for periocular identity verification

Beom Seok Oh, Kangrok Oh, Kar Ann Toh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

The periocular biometric comes into the spotlight recently due to several advantageous characteristics such as easily available and provision of crucial face information. However, many existing works are dedicated to extracting image features using texture based techniques such as local binary pattern (LBP). In view of the simplicity and effectiveness offered, this paper proposes to investigate into projection-based methods for periocular identity verification. Several well established projection-based methods such as principal component analysis, its variants and linear discriminant analysis will be adopted in our performance evaluation based on a subset of FERET face database. Our empirical results show that supervised learning methods significantly outperform those unsupervised learning methods and LBP in terms of equal error rate performance.

Original languageEnglish
Title of host publicationProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Pages871-876
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 - Singapore, Singapore
Duration: 2012 Jul 182012 Jul 20

Publication series

NameProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Other

Other2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
CountrySingapore
CitySingapore
Period12/7/1812/7/20

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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