Design and development of a robust (i.e., invariant to translations, rotations, and scale change), non-invasive, and contact-free biometric recognition system, which is able to identify a person from a digital image of the hand acquired by a low-resolution CMOS camera. The system involves a non-linear ordinary differential equation (ODE) aimed at extracting the feature vector, whilst the matching process makes use of the Pearson product-moment correlation coefficient to measure the similarity between the feature vectors.
Design and development of a robust, non-invasive, and touch-less palmprint-based biometric recognition system
Palma, David;Montessoro, Pier Luca
2014-01-01
Abstract
Design and development of a robust (i.e., invariant to translations, rotations, and scale change), non-invasive, and contact-free biometric recognition system, which is able to identify a person from a digital image of the hand acquired by a low-resolution CMOS camera. The system involves a non-linear ordinary differential equation (ODE) aimed at extracting the feature vector, whilst the matching process makes use of the Pearson product-moment correlation coefficient to measure the similarity between the feature vectors.File in questo prodotto:
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