Frequency and Color Fusion for Face Verification

Document Type

Article

Publication Date

12-1-2012

Abstract

A face verification method is presented in this chapter by fusing the frequency and color features for improving the face recognition grand challenge performance. In particular, the hybrid color space RIQ is constructed, according to the discriminating properties among the individual component images. For each component image, the frequency features are extracted from the magnitude, the real and imaginary parts in the frequency domain of an image. Then, an improved Fisher model extracts discriminating features from the frequency data for similarity computation using a cosine similarity measure. Finally, the similarity scores from the three component images in the RIQ color space are fused by means of a weighted summation at the decision level for the overall similarity computation. To alleviate the effect of illumination variations, an illumination normalization procedure is applied to the R component image. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 show the feasibility of the proposed frequency and color fusion method. © Springer-Verlag Berlin Heidelberg 2012.

Identifier

84885613996 (Scopus)

ISBN

[9783642284564]

Publication Title

Intelligent Systems Reference Library

External Full Text Location

https://doi.org/10.1007/978-3-642-28457-1_4

e-ISSN

18684408

ISSN

18684394

First Page

53

Last Page

71

Volume

37

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