Human identification using palm-vein images

Yingbo Zhou, Ajay Kumar Pathak

Research output: Journal article publicationJournal articleAcademic researchpeer-review

205 Citations (Scopus)

Abstract

This paper presents two new approaches to improve the performance of palm-vein-based identification systems presented in the literature. The proposed approach attempts to more effectively accommodate the potential deformations, rotational and translational changes by encoding the orientation preserving features and utilizing a novel region-based matching scheme. We systematically compare the previously proposed palm-vein identification approaches with our proposed ones on two different databases that are acquired with the contactless and touch-based imaging setup. We evaluate the performance improvement in both verification and recognition scenarios and analyze the influence of enrollment size on the performance. In this context, the proposed approaches are also compared for its superiority using single image enrollment on two different databases. The rigorous experimental results presented in this paper, on the databases of 100 and 250 subjects, consistently conforms the superiority of the proposed approach in both the verification and recognition scenario.
Original languageEnglish
Article number5783341
Pages (from-to)1259-1274
Number of pages16
JournalIEEE Transactions on Information Forensics and Security
Volume6
Issue number4
DOIs
Publication statusPublished - 1 Dec 2011

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications

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