Personal verification using palmprint and hand geometry biometric

  • Authors:

  • Ajay Kumar;David C. M. Wong;Helen C. Shen;Anil K. Jain

  • Affiliations:

  • Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;Pattern Recognition and Image Processing Lab, Department of Computer Science and Engineering, Michigan State University, East Lansing, MI

  • Venue:
  • AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
  • Year:
  • 2003

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Abstract

A new approach for the personal identification using hand images is presented. This paper attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike other bimodal biometric systems, the users does not have to undergo the inconvenience of passing through two sensors since the palmprint and hand geometry features can be are acquired from the same image, using a digital camera, at the same time. Each of these gray level images are aligned and then used to extract palmprint and hand geometry features. These features are then examined for their individual and combined performance. The image acquisition setup used in this work was inherently simple and it does not employ any special illumination nor does it use any pegs to cause any inconvenience to the users. Our experimental results on the image dataset from 100 users confirm the utility of hand geometry features with those from palmprints and achieve promising results with a simple image acquisition setup.