Enhanced multiband feature technique for face recognition under varying illumination

Sue Inn Ch'ng, Kah Phooi Seng, Li Minn Ang

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

2 Citations (Scopus)

Abstract

This paper presents an enhanced multiband feature technique to improve the performance of face recognition under varying illumination. First, the illumination invariant subbands are extracted using wavelet packet transform and multiband feature selector. Then, histogram equalization is applied to the selected subbands to enhance the contrast of the subband (global). To reduce the noise and enhance the fine details of the facial features (local), an unsharp filter is subsequently applied to the histogram equalized subband. The unsharp filter is created by combining a Gaussian low pass filter and a negative Laplacian operator. The recognition performance of the proposed enhancement scheme is validated against the Yale B database. An improvement in recognition rate has been observed when the enhancement scheme is compared to the original unenhanced subband.

Original languageEnglish
Title of host publicationIEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010 - Conference Booklet
Pages61-64
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventIEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010 - Kuala Lumpur, Malaysia
Duration: 20 Nov 201021 Nov 2010

Publication series

NameIEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010 - Conference Booklet

Conference

ConferenceIEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010
Country/TerritoryMalaysia
CityKuala Lumpur
Period20/11/1021/11/10

Keywords

  • Gaussian low pass filter
  • Laplacian operator
  • Multi band feature technique
  • Wavelet packet transform

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