Title :
Biometric Identification through Hand Geometry
Author :
Hashemi, Javad ; Fatemizadeh, Emad
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran
Abstract :
A new approach for person identification based on hand geometry is presented. After preprocessing hand features are extracted from a photograph taken while user has placed his/her hand (either left or right) on the platform of a document scanner with no limits or fixation. Different pattern recognition techniques like Gaussian mixture modeling (GMM), radial basis function neural networks (RBF), multilayer perceptron (MLP), k-nearest neighbor (k-NN), Bayes method and Mahalanobis/Hamming distance have been used in classification section. Experimental results show a rate of success above 90%
Keywords :
Bayes methods; Gaussian processes; biometrics (access control); feature extraction; image recognition; multilayer perceptrons; pattern classification; radial basis function networks; Bayes method; Gaussian mixture modeling; Hamming distance; Mahalanobis distance; biometric identification; document scanner; hand feature extraction; hand geometry; image classification; k-nearest neighbor; multilayer perceptron; pattern recognition; person identification; radial basis function neural networks; Biometrics; Costs; Feature extraction; Fingerprint recognition; Fingers; Geometry; Image databases; Iris; Java; Retina; Biometric; GMMs; Hand geometry; RBF neural networks;
Conference_Titel :
Computer as a Tool, 2005. EUROCON 2005.The International Conference on
Conference_Location :
Belgrade
Print_ISBN :
1-4244-0049-X
DOI :
10.1109/EURCON.2005.1630119
