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SCIA
2009
Springer

Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition

4 years 2 months ago
Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition
A feature extraction method using multi-frequency bands is proposed for face recognition, named as the Multi-band Gradient Component Pattern (MGCP). The MGCP captures discriminative information from Gabor filter responses in virtue of an orthogonal gradient component analysis method, which is especially designed to encode energy variations of Gabor magnitude. Different from some well-known Gabor-based feature extraction methods, MGCP extracts geometry features from Gabor magnitudes in the orthogonal gradient space in a novel way. It is shown that such features encapsulate more discriminative information. The proposed method is evaluated by performing face recognition experiments on the FERET and FRGC ver 2.0 databases and compared with several state-of-the-art approaches. Experimental results demonstrate that MGCP achieves the highest recognition rate among all the compared methods, including some well-known Gabor-based methods.
Yimo Guo, Jie Chen, Guoying Zhao, Matti Pietik&aum
Added 27 Jul 2010
Updated 27 Jul 2010
Type Conference
Year 2009
Where SCIA
Authors Yimo Guo, Jie Chen, Guoying Zhao, Matti Pietikäinen, Zhengguang Xu
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