Using genetic algorithms to find person-specific Gabor feature detectors for face indexing and recognition

Sreekar Krishna, John Black, Sethuraman Panchanathan

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

5 Scopus citations


In this paper, we propose a novel methodology for face recognition, using person-specific Gabor wavelet representations of the human face. For each person in a face database a genetic algorithm selects a set of Gabor features (each feature consisting of a particular Gabor wavelet and a corresponding (x, y) face location) that extract facial features that are unique to that person. This set of Gabor features can then be applied to any normalized face image, to determine the presence or absence of those characteristic facial features. Because a unique set of Gabor features is used for each person in the database, this method effectively employs multiple feature spaces to recognize faces, unlike other face recognition algorithms in which all of the face images are mapped into a single feature space. Face recognition is then accomplished by a sequence of face verification steps, in which the query face image is mapped into the feature space of each person in the database, and compared to the cluster of points in that space that represents that person. The space in which the query face image most closely matches the cluster is used to identify the query face image. To evaluate the performance of this method, it is compared to the most widely used subspace method for face recognition: Principle Component Analysis (PCA). For the set of 30 people used in this experiment, the face recognition rate of the proposed method is shown to be substantially higher than PCA.

Original languageEnglish (US)
Title of host publicationAdvances in Biometrics - International Conference, ICB 2006, Proceedings
Number of pages10
StatePublished - Jun 15 2006
EventInternational Conference on Biometrics, ICB 2006 - Hong Kong, China
Duration: Jan 5 2006Jan 7 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3832 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Conference on Biometrics, ICB 2006
CityHong Kong

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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