%0 Journal Article
%T People Recognition by RGB and NIR Analysis from Digital Image Database Using Cross-Correlation and Wavelets
%A David Mart&#237
%A nez-Mart&#237
%A nez
%A Yedid Erandini Ni&#241
%A o-Membrillo
%A Jos&#233
%A Francisco Sol&#237
%A s-Villarreal
%A Oscar Espinoza-Ortega
%A Lizbeth Sandoval-Ju&#225
%A rez
%A Francisco Javier N&#250
%A &#241
%A ez-Garc&#237
%A a
%J Engineering
%P 353-359
%@ 1947-394X
%D 2024
%I Scientific Research Publishing
%R 10.4236/eng.2024.1610026
%X This document presents a framework for recognizing people by palm vein distribution analysis using cross-correlation based signatures to obtain descriptors. Haar wavelets are useful in reducing the number of features while maintaining high recognition rates. This experiment achieved 97.5% of individuals classified correctly with two levels of Haar wavelets. This study used twelve-version of RGB and NIR (near infrared) wavelength images per individual. One hundred people were studied; therefore 4,800 instances compose the complete database. A Multilayer Perceptron (MLP) was trained to improve the recognition rate in a k-fold cross-validation test with k = 10. Classification results using MLP neural network were obtained using Weka (open source machine learning software).
%K Palm Vein Recognition
%K Cross-Correlation
%K Haar Wavelets
%K Multilayer Perceptron
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=136913