Image alignment based on invariant features for palmprint identification

Wenxin Li, Dapeng Zhang, Zhuoqun Xu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

32 Citations (Scopus)

Abstract

Palmprint identification provides a new technique for personal authentication. Previous research on palmprint identification mainly focuses on feature extraction and representation (Pattern Recognition 33(4) (1999) 691). But a crucial issue, palmprint alignment, is not addressed. Palmprint alignment involves moving and rotating the palmprints to locate at their correct position with the same direction. By this alignment operation, a certain palmprint sub-area can be easily obtained so that the corresponding palmprint feature matching will be carried out satisfactorily. In order to align palmprints, two invariant features, outer boundary direction and end point of heart line, are introduced. The key point in this paper is to propose a new automatic invariant-feature-based palmprint alignment method, which is able to deal with various image distortions such as image rotation and shift. This method provides a foundation for further feature extraction and matching. The experimental results demonstrate the effectiveness and accuracy of the proposed method.
Original languageEnglish
Pages (from-to)373-379
Number of pages7
JournalSignal Processing: Image Communication
Volume18
Issue number5
DOIs
Publication statusPublished - 1 May 2003

Keywords

  • Biometric computing
  • Image segmentation
  • Invariant feature extraction
  • Palmprint alignment
  • Palmprint verification

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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