Personal authentication using palm-print features

摘要

Biometrics-based authentication is a verification approach using the biological features inherent in each individual. They are processed based on the identical, portable. and arduous duplicate characteristics. In this paper, we propose a scanner-based personal authentication system by using the palm-print features. It is very suitable in many network-based applications. The authentication system consists of enrollment and verification stages. In the enrollment stage, the training samples are collected and processed by the pre-processing, feature extraction, and modeling modules to generate the matching templates. In the verification stage, a query sample is also processed by the pre-processing and feature extraction modules, and then is matched with the reference templates to decide whether it is a genuine sample or not. The region of interest (ROI) for each sample is first obtained from the pre-processing module. Then, the palm-print features are extracted from the ROI by using Sobel and morphological operations. The reference templates for a specific user are generated in the modeling module. Last, we use the template-matching and the backpropagation neural network to measure the similarity in the verification stage. Experimental results verify the validity of our proposed approaches in personal authentication. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 15]