JOURNAL OF MULTIMEDIA (JMM)
ISSN : 1796-2048
Volume : 4 Issue : 4 Date : August 2009
Face Recognition by Extending Elastic Bunch Graph Matching with Particle Swarm Optimization
Rajinda Senaratne, Saman Halgamuge, and Arthur Hsu
Full Text: PDF (1,332 KB)
Elastic Bunch Graph Matching is one of the well known methods proposed for face recognition. In
this work, we propose several extensions to Elastic Bunch Graph Matching and its recent variant
Landmark Model Matching. We used data from the FERET database for experimentations and to
compare the proposed methods.
We apply Particle Swarm Optimization to improve the face graph matching procedure in Elastic
Bunch Graph Matching method and demonstrate its usefulness. Landmark Model Matching
depends solely on Gabor wavelets for feature extraction to locate the landmarks (facial feature
points). We show that improvements can be made by combining gray-level profiles with Gabor
wavelet features for feature extraction. Furthermore, we achieve improved recognition rates by
hybridizing Gabor wavelet with eigenface features found by Principal Component Analysis, which
would provide information contained in the overall appearance of a face. We use Particle Swarm
Optimization to fine tune the hybridization weights.
Results of both fully automatic and partially automatic versions of all methods are presented. The
best-performing method improves the recognition rate up to 22.6% and speeds up the processing
time by 8 times over the Elastic Bunch Graph Matching for the fully automatic case.
Eigenfaces, Elastic Bunch Graph Matching, Face Recognition, Gabor wavelets, Hybridization,
Particle Swarm Optimization, and Principal Component Analysis