Simplified Gabor wavelets for human face recognition

Wing Pong Choi, Siu Hong Tse, Kwok Wai Wong, Kin Man Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

74 Citations (Scopus)


Gabor wavelets (GWs) are commonly used for extracting local features for various applications such as object detection, recognition and tracking. However, extracting Gabor features is computationally intensive, so the features are impractical for real-time applications. In this paper, we propose a simplified version of Gabor wavelets (SGWs) and an efficient algorithm for extracting the features based on an integral image. We evaluate the performance of the SGW features for face recognition. Experimental results show that using SGWs can achieve a performance level similar to using GWs, while the runtime for feature extraction using SGWs is, at most, 4.39 times faster than that of GWs implemented by using the fast Fourier transform (FFT).
Original languageEnglish
Pages (from-to)1186-1199
Number of pages14
JournalPattern Recognition
Issue number3
Publication statusPublished - 1 Mar 2008


  • Feature extraction
  • Gabor wavelets
  • Simplified Gabor wavelets

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering


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