Wavelet local binary patterns fusion as illuminated facial image preprocessing for face verification

Yi Zheng Goh, Andrew Beng Jin Teoh, Michael Kah Ong Goh

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


Poor illumination condition is recognized as one of the major problem in contemporary two-dimensional (2D) face verification system. It causes large variation in facial images and degrades the performance of the system. Many works of resolving illumination variation in face verification have been reported in the past decades. In this paper, a facial image illumination invariant technique is devised based on the fusion of wavelet analysis and local binary patterns. Particularly, illumination-reflectance model is used to detach illumination and reflectance components with multi-resolution nature of wavelet analysis. The illumination component that resides in low spatial-frequency wavelet subband is first rid off efficiently. The reflectance components that reside in high and middle spatial-frequency wavelet subbands are enhanced with local binary patterns histogram. Finally, two processed images are fused through wavelet image fusion. This technique works out promisingly in achieving better recognition results on YaleB, CMU PIE and FRGC face databases in comparison with existing illumination invariant techniques.

Original languageEnglish
Pages (from-to)3959-3972
Number of pages14
JournalExpert Systems with Applications
Issue number4
Publication statusPublished - 2011 Apr

Bibliographical note

Funding Information:
This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University (Grant Number: R112002105080020 ).

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence


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