Personal identification using multibiometrics rank-level fusion

Ajay Kumar Pathak, Sumit Shekhar

Research output: Journal article publicationJournal articleAcademic researchpeer-review

93 Citations (Scopus)

Abstract

This paper investigates a new approach for the personal recognition using rank-level combination of multiple biometrics representations. There has been very little effort to study rank-level fusion approaches for multibiometrics combination and none using multiple palmprint representations. In this paper, we propose a new nonlinear rank-level fusion approach and present a comparative study of rank-level fusion approaches, which can be useful in combining multibiometrics fusion. The comparative experimental results from the publicly available multibiometrics scores and real hand biometrics data to evaluate/ascertain the rank-level combination using Borda count, logistic regression/weighted Borda count, highest rank method, and Bucklin method are presented. Our experimental results presented in this paper suggest that significant performance improvement in the recognition accuracy can be achieved as compared to those from individual palmprint representations. The rigorous experimental results presented in this paper also suggest that the proposed nonlinear rank-level approach outperforms the rank-level combination approaches presented in this paper.
Original languageEnglish
Article number5675697
Pages (from-to)743-752
Number of pages10
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Volume41
Issue number5
DOIs
Publication statusPublished - 1 Sep 2011

Keywords

  • Biometrics
  • multibiometrics
  • palmprint recognition
  • personal identification
  • rank-level fusion

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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