Hand Geometry Based Recognition with a MLP Classifier
Abstract
This paper presents a biometric recognition system based on hand geometry. We describe a database specially collected for research purposes, which consists of 50 people and 10 different acquisitions of the right hand. This database can be freely downloaded. In addition, we describe a feature extraction procedure and we obtain experimental results using different classification strategies based on Multi Layer Perceptrons (MLP). We have evaluated identification rates and Detection Cost Function (DCF) values for verification applications. Experimental results reveal up to 100% identification and 0% DCF
Cite
@article{arxiv.2204.08469,
title = {Hand Geometry Based Recognition with a MLP Classifier},
author = {Marcos Faundez-Zanuy and Miguel A. Ferrer-Ballester and Carlos M. Travieso-González and Virginia Espinosa-Duro},
journal= {arXiv preprint arXiv:2204.08469},
year = {2022}
}
Comments
8 pages published in International Conference on Biometrics ICB 2006, Advances in Biometrics pages 721 727 Hong Kong, China. arXiv admin note: substantial text overlap with arXiv:2204.07764