Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44067
Title: Fingers shape biometric identification using Point Distribution Models
Authors: Ferrer, M. A. 
Morales, A.
Alonso, J. B. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: biometrics (access control) , eigenvalues and eigenfunctions , fingerprint identification , least squares approximations , shape recognition , support vector machines
Issue Date: 2010
Publisher: 0013-5194
Journal: Electronics letters 
Abstract: 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.
URI: http://hdl.handle.net/10553/44067
ISSN: 0013-5194
DOI: 10.1049/el.2010.2086
Source: Electronics Letters[ISSN 0013-5194],v. 46, p. 495-497
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