Mohd.Abdul Muqeet; Raghunath S.Holambe

Enhancing Face Recognition Performance using Triplet Half Band Wavelet Filter Bank

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Author(s)

Mohd.Abdul Muqeet ^1,* Raghunath S.Holambe ²

1. Muffakham Jah College of Engineering and Technology, Hyderabad, India

2. SGGS Institute of Engineering and Technology, Nanded, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2016.12.08

Received: 12 Aug. 2016 / Revised: 22 Sep. 2016 / Accepted: 2 Nov. 2016 / Published: 8 Dec. 2016

Index Terms

Face Recognition, triplet half band wavelet filter bank (TWFB), PCA, KPCA, LDA, KDA

Abstract

Face recognition using subspace methods are quite popular in research community. This paper proposes an efficient face recognition method based on the application of recently developed triplet half band wavelet filter bank (TWFB) as pre-processing step to further enhance the performance of well known linear and nonlinear subspace methods such as principle component analysis(PCA),kernel principle component analysis (KPCA), linear discriminant analysis (LDA), and kernel discriminant analysis (KDA). The design of 6th order TWFB is used as the multiresolution analysis tool to perform the 2-D discrete wavelet transform (DWT). Experimental results are performed on two standard databases ORL and Yale. Comparative results are obtained in terms of verification performance parameters such as false acceptance rate (FAR), false rejection rate (FRR) and genuine acceptance rate (GAR). Application of TWFB enhances the performance of PCA, KPCA, LDA, and KDA based methods.

Cite This Paper

Mohd.Abdul Muqeet, Raghunath S.Holambe,"Enhancing Face Recognition Performance using Triplet Half Band Wavelet Filter Bank", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.8, No.12, pp.62-70, 2016. DOI: 10.5815/ijigsp.2016.12.08

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International Journal of Image, Graphics and Signal Processing (IJIGSP)