An Illumination Invariant Bimodal Method Employing Discriminant Features for Face Recognition

JiYing WU  QiuQi RUAN  Gaoyun AN 

Publication
IEICE TRANSACTIONS on Information and Systems  Vol.E92-D  No.2  pp.365-368
Publication Date: 2009/02/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
Keyword: 
enhanced gray level image,  illumination invariant image,  discriminant feature extraction,  image fusion, 

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Summary: 
A novel bimodal method for face recognition under low-level lighting conditions is proposed. It fuses an enhanced gray level image and an illumination-invariant geometric image at the feature-level. To further improve the recognition performance under large variations in attributions such as poses and expressions, discriminant features are extracted from source images using the wavelet transform-based method. Features are adaptively fused to reconstruct the final face sample. Then FLD is used to generate a supervised discriminant space for the classification task. Experiments show that the bimodal method outperforms conventional methods under complex conditions.