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A Spectral Domain Local Feature Extraction Algorithm for Face Recognition
Shaikh Anowarul Fattah, Hafiz Imtiaz
Pages - 62 - 73     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 5   Issue - 2    |    Publication Date - July / August 2011  Table of Contents
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KEYWORDS
Feature Extraction, Classification, Two Dimensional Discrete Fourier Transform, Dominant Spectral Feature, Face Recognition, Modularization
ABSTRACT
In this paper, a spectral domain feature extraction algorithm for face recognition is proposed, which efficiently exploits the local spatial variations in a face image. For the purpose of feature extraction, instead of considering the entire face image, an entropy-based local band selection criterion is developed, which selects high-informative horizontal bands from the face image. In order to capture the local variations within these high-informative horizontal bands precisely, a feature selection algorithm based on two-dimensional discrete Fourier transform (2D-DFT) is proposed. Magnitudes corresponding to the dominant 2D-DFT coefficients are selected as features and shown to provide high within-class compactness and high between-class separability. A principal component analysis is performed to further reduce the dimensionality of the feature space. Extensive experimentations have been carried out upon standard face databases and the recognition performance is compared with some of the existing face recognition schemes. It is found that the proposed method offers not only computational savings but also a very high degree of recognition accuracy.
CITED BY (3)  
1 Rakesh, S. M., Sandeep, G. S. P., Manikantan, K., & Ramachandran, S. (2013, January). DFT-Based Feature Extraction and Intensity Mapped Contrast Enhancement for Enhanced Iris Recognition. In Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012) (pp. 481-494). Springer India.
2 Piñol, M., Sappa, A. D., & Toledo, R. (2013, January). Multi-Table Reinforcement Learning for Visual Object Recognition. In Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012) (pp. 469-479). Springer India.
3 Shah, S., Khan, S. A., & Riaz, N. (2013). Analytical Study of Face Recognition Techniques.
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Dr. Shaikh Anowarul Fattah
Bangladesh University of Engineering and Technology - Bangladesh
sfattah@princeton.edu
Mr. Hafiz Imtiaz
Bangladesh University of Engineering and Technology - Bangladesh