Frequency and Color Fusion for Face Verification

Zhiming Liu, Chengjun Liu

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationCross Disciplinary Biometric Systems
EditorsChengjun Liu, Vijay Kumar Mago
Pages53-71
Number of pages19
DOIs
StatePublished - 2012

Publication series

NameIntelligent Systems Reference Library
Volume37
ISSN (Print)1868-4394
ISSN (Electronic)1868-4408

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Information Systems and Management
  • Library and Information Sciences

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