Perfecting a Video Game with Game Metrics
Vol 10, No 1: March 2012

Gabor-based Face Recognition with Illumination Variation using Subspace-Linear Discriminant Analysis

Hendra Kusuma (Institut Teknologi Sepuluh Nopember Surabaya)
Wirawan Wirawan (Institut Teknologi Sepuluh Nopember Surabaya)
Adi Soeprijanto (Institut Teknologi Sepuluh Nopember Surabaya)



Article Info

Publish Date
01 Mar 2012

Abstract

            Face recognition has been an active research topic in the past few decades due to its potential applications. Accurate face recognition is still a difficult task, especially in the case that illumination is unconstrained. This paper presents an efficient method for the recognition of faces with different illumination by using Gabor features, which are extracted by using log-Gabor filters of six orientations and four scales. By Using sliding window algorithm, these features are extracted at image block-regions. Extracted features are passed to the principal component analysis (PCA) and then to linear discriminant analysis (LDA). For development and testing we used facial images from the Yale-B databases. The proposed method achieved 86–100 % rank 1 recognition rate.

Copyrights © 2012






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...