Radius based block local binary pattern on T-zone face area for face recognition

Md. Jan Nordin, Abdul Aziz Abdul K Hamid, Sumazly Ulaiman, R. U. Gobithaasan

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This study presents a comparison of recognition performance between feature extraction on the T-Zone face area and Radius based block on the critical point. A T-Zone face image is first divided into small regions where Local Binary Pattern (LBP) histograms are extracted and then concatenated into a single feature vector. This feature vector will further reduce the dimensionality scope by using the well established Principle Component Analysis (PCA) technique. On the other hand, while the original LBP techniques focus in dividing the whole image into certain regions, we proposed a new scheme, which focuses on critical region, which gives more impact to the recognition performance. This technique is known as Radius Based Block Local Binary Pattern (RBB-LBP). Here we focus on three main area which is eye (including eyebrow), mouth and nose. We defined four critical point represent left eye, right eye, nose and mouth, from this four main point we derived the next nine point. This approach will automatically create the redundancy in various regions and for every radius size window a robust histogram with all possible labels constructed. Experiments have been carried out on the different sets of the Olivetti Research Laboratory (ORL) database. RBB-LBP obtained high recognition rates when compared to standard LBP, LBP+PCA and also on T-Zone area. Our result shows of 16% improvement compared with LBP+PCA and 6% improvement compared with LBP. Our studies proves that the RBB-LBP method, reduce the length of the feature vector, while the recognition performance is improved.

Original languageEnglish
Pages (from-to)2525-2537
Number of pages13
JournalJournal of Computer Science
Volume10
Issue number12
DOIs
Publication statusPublished - 2014

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Face recognition
Research laboratories
Redundancy
Feature extraction
Labels
Experiments

Keywords

  • Face recognition
  • Local binary pattern
  • ORL
  • Principle component analysis
  • RBB-LBP

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Radius based block local binary pattern on T-zone face area for face recognition. / Nordin, Md. Jan; Hamid, Abdul Aziz Abdul K; Ulaiman, Sumazly; Gobithaasan, R. U.

In: Journal of Computer Science, Vol. 10, No. 12, 2014, p. 2525-2537.

Research output: Contribution to journalArticle

Nordin, Md. Jan ; Hamid, Abdul Aziz Abdul K ; Ulaiman, Sumazly ; Gobithaasan, R. U. / Radius based block local binary pattern on T-zone face area for face recognition. In: Journal of Computer Science. 2014 ; Vol. 10, No. 12. pp. 2525-2537.
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