Face recognition using independent gabor wavelet features

Chengjun Liu, Harry Wechsler

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

5 Scopus citations


We introduce in this paper a novel Independent Gabor wavelet Features (IGF) method for face recognition. The IGF method derives first an augmented Gabor feature vector based upon the Gabor wavelet transformation of face images and using different orientation and scale local features. Independent Component Analysis (ICA) operates then on the Gabor feature vector subject to sensitivity analysis for the ICA transformation. Finally, the IGF method applies the Probabilistic Reasoning Model for classification by exploiting the independence properties between the feature components derived by the ICA. The feasibility of the new IGF method has been successfully tested on face recognition using 600 FERET frontal face images corresponding to 200 subjects whose facial expressions and lighting conditions may vary.

Original languageEnglish (US)
Title of host publicationAudio- and Video-Based Biometric Person Authentication - Third International Conference, AVBPA 2001, Proceedings
PublisherSpringer Verlag
Number of pages6
ISBN (Print)3540422161, 9783540422167
StatePublished - 2001
Externally publishedYes
Event3rd International Conference on Audio- and Video- Based Biometric Person Authentication, AVBPA 2001 - Halmstad, Sweden
Duration: Jun 6 2001Jun 8 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2091 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other3rd International Conference on Audio- and Video- Based Biometric Person Authentication, AVBPA 2001

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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