Improving the interest operator for face recognition

Yong Xu, Lu Yao, Dapeng Zhang, Jing Yu Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)


When the conventional interest operator is used as the feature extraction procedure of face recognition, it has the following two shortcomings: first, though the purpose of the conventional interest operator is to use the intensity variation between neighboring pixels to represent the image, it cannot obtain all variation information between neighboring pixels. Second, under varying lighting conditions two images of the same face usually have different feature extraction results even though the face itself does not have obvious change. In this paper, we propose two new interest operators for face recognition, which are used to calculate the pixel intensity variation information of overlapping blocks produced from the original face image. The following two factors allow the new operators to perform better than the conventional interest operator: the first factor is that by taking the relative rather than absolute variation of the pixel intensity as the feature of an image block, the new operators can obtain robust block features. The second factor is that the scheme to partition an image into overlapping rather than non-overlapping blocks allows the proposed operators to produce more representation information for the face image. Experimental results show that the proposed operators offer significant accuracy improvement over the conventional interest operator.
Original languageEnglish
Pages (from-to)9719-9728
Number of pages10
JournalExpert Systems with Applications
Issue number6
Publication statusPublished - 1 Aug 2009


  • Face recognition
  • Feature extraction
  • Interest operator

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence


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