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An Illumination Invariant Bimodal Method Employing Discriminant Features for Face Recognition
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
enhanced gray level image,
illumination invariant image,
discriminant feature extraction,
Full Text: PDF
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.