Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2011-10-07
Signal and Image Processing: An International Journal, Vol. 2, No. 3, Sept 2011
Computer Science
Computer Vision and Pattern Recognition
12 pages, 12 figures, Published in Signal and Image Processing: An International Journal Vol 2 No 3
Scientific paper
In this paper, a multi-resolution feature extraction algorithm for face recognition is proposed based on two-dimensional discrete wavelet transform (2D-DWT), 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 segments from the face image. In order to capture the local spatial variations within these highinformative horizontal bands precisely, the horizontal band is segmented into several small spatial modules. Dominant wavelet coefficients corresponding to each local region residing inside those horizontal bands are selected as features. In the selection of the dominant coefficients, a threshold criterion is proposed, which not only drastically reduces the feature dimension but also provides 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 experimentation is carried out upon standard face databases and a very high degree of recognition accuracy is achieved by the proposed method in comparison to those obtained by some of the existing methods.
Fattah Shaikh Anowarul
Imtiaz Hafiz
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