Matching of palmprints

  • Authors:
  • Nicolae Duta;Anil K. Jain;Kanti V. Mardia

  • Affiliations:
  • Speech and Language Processing Department, BBN Technologies, 70 Fawcett Street, Cambridge, MA;Department of Computer Science and Engineering, Michigan State University, 3115 Engineering Building, East Lansing, MI;Department of Statistics, The University of Leeds, Leeds, West Yorkshire, LS2 9JT, UK

  • Venue:
  • Pattern Recognition Letters - In memory of Professor E.S. Gelsema
  • Year:
  • 2002

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Abstract

This paper investigates the feasibility of person identification based on feature points extracted from palmprint images. Our approach first extracts a set of feature points along the prominent palm lines (and the associated line orientation) from a given palmprint image. Next we decide if two palmprints belong to the same hand by computing a matching score between the corresponding sets of feature points of the two palmprints. The two sets of feature points/ orientations are matched using our previously developed point matching technique which takes into account the non-linear deformations as well as the outlier points present in the two sets. The estimates of the matching score distributions for the genuine and imposter sets of palm pairs showed that palmprints have a good discrimination power. The overlap between the genuine and imposter distributions was found to be about 5%. Our preliminary results indicate that adding palmprint information may improve the identity verification provided by fingerprints in cases where fingerprint images cannot be properly acquired (e.g., due to dry skin).