Principal line based ICP alignment for palmprint verification

Wei Li, Lei Zhang, Dapeng Zhang, Jingqi Yan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

14 Citations (Scopus)


Image alignment is a crucial step in palmprint verification. However, most of the existing palmprint alignment methods use only some key points between fingers or in palm boundary to extract the region of interest (ROI), which is consequently used for feature extraction and matching. Such alignment methods can only give a coarse alignment of the palmprint images. This paper presents a new effective refinement method for palmprint alignment by adapting the iterative closest point (ICP) method to the palmprint principal lines. The proposed method offers a more accurate alignment of palmprints by correcting efficiently the shifting, rotation and scaling variations introduced in data acquisition. The experimental results show that the proposed method can greatly improve the palmprint verification accuracy in real time.
Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)9781424456543
Publication statusPublished - 1 Jan 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 7 Nov 200910 Nov 2009


Conference2009 IEEE International Conference on Image Processing, ICIP 2009


  • Biometrics
  • ICP
  • Image alignment
  • Line extraction
  • Palmprint recognition

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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