Hierarchical palmprint identification via multiple feature extraction

Jia You, Wenxin Li, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

231 Citations (Scopus)

Abstract

Biometric computing offers an effective approach to identify personal identity by using individual's unique, reliable and stable physical or behavioral characteristics. This paper describes a new method to authenticate individuals based on palmprint identification and verification. Firstly, a comparative study of palmprint feature extraction is presented. The concepts of texture feature and interesting points are introduced to define palmprint features. A texture-based dynamic selection scheme is proposed to facilitate the fast search for the best matching of the sample in the database in a hierarchical fashion. The global texture energy, which is characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination, is used to guide the dynamic selection of a small set of similar candidates from the database at coarse level for further processing. An interesting point based image matching is performed on the selected similar patterns at fine level for the final confirmation. The experimental results demonstrate the effectiveness and accuracy of the proposed method.
Original languageEnglish
Pages (from-to)847-859
Number of pages13
JournalPattern Recognition
Volume35
Issue number4
DOIs
Publication statusPublished - 1 Apr 2002

Keywords

  • Biometric computing
  • Feature extraction
  • Image matching
  • Interesting points
  • Palmprint classification
  • Texture features

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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