Extracting efficient color features for face recognition using evolutionary computation

Peichung Shih, Chengjun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper presents an evolutionary framework as a novel color feature extraction method for face recognition. First, two new color spaces are defined as linear transformations of the input RGB color space. The first color space is defined by one luminance (L) channel and two chrominance channels (C 1,C 2), and the second color space incorporates one luminance channel (L) and three chrominance channels (C 1,C 2,C 3). Genetic Algorithms (GAs), driven by a fitness function that evaluates face recognition accuracy, thus search for the optimal transformations from the RGB color space to the LC 1C 2 and the LC 1C 2C 3 color spaces, respectively. The successful application of the proposed evolutionary framework is demonstrated with the Face Recognition Grand Challenge (FRGC) databases and the Biometric Experimentation Environment (BEE) baseline algorithm. In particular, when using an FRGC version 1 dataset containing 366 training images, 152 controlled gallery images, and 608 uncontrolled probe images, the evolutionary framework improves the rank-one face verification rate of the BEE baseline algorithm from 37% to 77%. When applied to an FRGC version 2 dataset consisting of 6,660 training images, 16,028 controlled target images, and 8,014 uncontrolled query images, the evolutionary framework improves the face verification rate (at 0.1% false acceptance rate) of the BEE baseline algorithm from 13% to 37%.

Original languageEnglish (US)
Title of host publicationProceedings - Sixth International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2005
Pages285-290
Number of pages6
DOIs
StatePublished - Dec 1 2005
Event6th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2005 - Las Vegas, NV, United States
Duration: Aug 16 2005Aug 18 2005

Other

Other6th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2005
CountryUnited States
CityLas Vegas, NV
Period8/16/058/18/05

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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