Simplified Gabor wavelets for efficient feature extraction

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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Gabor wavelets (GWs) are commonly used for extracting local features for various applications like 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 SGWs for face recognition. Experimental results show that SGWs can achieve a performance level similar to GWs, while the runtime for feature extraction using SGWs is about 4.39 times faster than that of GWs, implemented by using fast Fourier transform (FFT).
Original languageEnglish
Title of host publicationTENCON 2007 - 2007 IEEE Region 10 Conference
Publication statusPublished - 1 Dec 2007
EventIEEE Region 10 Conference, TENCON 2007 - Taipei, Taiwan
Duration: 30 Oct 20072 Nov 2007


ConferenceIEEE Region 10 Conference, TENCON 2007

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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