A hybrid color and frequency features method for face recognition

Document Type

Article

Publication Date

10-1-2008

Abstract

This correspondence presents a novel hybrid Color and Frequency Features (CFF) method for face recognition. The CFF method, which applies an Enhanced Fisher Model (EFM), extracts the complementary frequency features in a new hybrid color space for improving face recognition performance. The new color space, the RIQ color space, which combines the R component image of the RGB color space and the chromatic components I and Q of the YIQ color space, displays prominent capability for improving face recognition performance due to the complementary characteristics of its component images. The EFM then extracts the complementary features from the real part, the imaginary part, and the magnitude of the R image in the frequency domain. The complementary features are then fused by means of concatenation at the feature level to derive similarity scores for classification. The complementary feature extraction and feature level fusion procedure applies to the I and Q component images as well. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 show that i) the hybrid color space improves face recognition performance significantly, and ii) the complementary color and frequency features further improve face recognition performance. © 2008 IEEE.

Identifier

52649094942 (Scopus)

Publication Title

IEEE Transactions on Image Processing

External Full Text Location

https://doi.org/10.1109/TIP.2008.2002837

ISSN

10577149

PubMed ID

18784044

First Page

1975

Last Page

1980

Issue

10

Volume

17

Fund Ref

U.S. Department of Justice

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