Biometric recognition using entropy-based discretization

Ajay Kumar Pathak, Dapeng Zhang

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

4 Citations (Scopus)

Abstract

The biometrics based recognition systems proposed in the literature have not yet exploited user-specific dependencies in the feature level representation. This paper suggests and investigates the performance improvement of the existing biometric systems using the discretization of extracted features. The performance improvement due to the unsupervised and supervised discretization schemes is compared on verity of classifiers; KNN, naïve Bayes, SVM and FFN. The experimental results on the hand-geometry database of 100 users achieve significant improvement in the recognition accuracy and confirm the usefulness of discretization in biometrics systems.
Original languageEnglish
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Volume2
DOIs
Publication statusPublished - 6 Aug 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: 15 Apr 200720 Apr 2007

Conference

Conference2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/TerritoryUnited States
CityHonolulu, HI
Period15/04/0720/04/07

Keywords

  • Biometrics
  • Feature discretization
  • Feature representation
  • Hand geometry
  • Personal recognition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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