Gabor-DCT Features with Application to Face Recognition

Zhiming Liu, Chengjun Liu

Research output: Chapter in Book/Report/Conference proceedingChapter


This chapter presents a Gabor-DCT Features (GDF) method on color facial parts for face recognition. The novelty of the GDF method is fourfold. First, four discriminative facial parts are used for dealing with image variations. Second, the Gabor filtered images of each facial part are grouped together based on adjacent scales and orientations to form a Multiple Scale and Multiple Orientation Gabor Image Representation (MSMO-GIR). Third, each MSMO-GIR first undergoes Discrete Cosine Transform (DCT) with frequency domain masking for dimensionality and redundancy reduction, and then is subject to discriminant analysis for extracting the Gabor-DCT features. Finally, at the decision level, the similarity scores derived from all the facial parts as well as from the Gabor filtered whole face image are fused together by means of the sum rule. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 and the CMU Multi-PIE database show the feasibility of the proposed GDF method.

Original languageEnglish (US)
Title of host publicationCross Disciplinary Biometric Systems
EditorsChengjun Liu, Vijay Kumar Mago
Number of pages17
StatePublished - 2012

Publication series

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

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Information Systems and Management
  • Library and Information Sciences


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