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Fingers shape biometric identification using Point Distribution Models

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3 Author(s)
M. A. Ferrer ; Department of Senales y Comunicaciones, Centro Tecnologico para la Innovacion en Comunicaciones, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, Las Palmas de Gran Canaria E35017, Spain ; A. Morales ; J. B. Alonso

A hand profile characterisation approach for biometric identification with contactless hand image acquisition is evaluated. The approach models the shapes of fingers with Point Distribution Models (PDMs), which consist of a mean shape and a number of eigenvectors which describe the main modes of variation of the shape class. The weighted PDM eigenvectors that capture the variation between the input finger shapes and the averaged finger shapes are used as feature vectors. Classification is performed using a least squares support vector machine. Experiments using multiple hand databases demonstrated the advantage of using finger PDMs.

Published in:

Electronics Letters  (Volume:46 ,  Issue: 7 )