Feature extraction using Gabor feature-based IFDA

In this paper, we propose a new method of Gabor feature-based inverse Fisher discriminant analysis for face recognition. In the proposed method, the intrinsic feature is first characterized using Gabor wavelet transform with different scales and directions. Then, image discriminant features are extr...

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Bibliographic Details
Main Authors: Jinxia Ni, Zhongxi Sun
Format: Conference Proceeding
Language:English
Subjects:
Face
Face recognition
Feature extraction
Principal component analysis
Wavelet transforms
Online Access:Request full text
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Summary:In this paper, we propose a new method of Gabor feature-based inverse Fisher discriminant analysis for face recognition. In the proposed method, the intrinsic feature is first characterized using Gabor wavelet transform with different scales and directions. Then, image discriminant features are extracted by selecting principal components and inverse Fisher disciminant vectors. Experimental results on ORL and FERET face database demonstrate the effectiveness of the proposed method.
DOI:10.1109/ICICIP.2011.6008225