基于BP神经网络的指纹模板分类器分类算法  

A New Classifiable Algorithm of Fingerprint Template Based on Backpropagation Neural Networks

作　　者：蔡俊[1] 赵建民[1] 周红晓[1] 任德官[1] 

机构地区：[1]浙江师范大学计算机科学与工程学院,金华321004

出　　处：《计算机科学》2002年第9期80-81,共2页Computer Science

基　　金：浙江省自然科学基金(ZD0108)

摘　　要：一、引言 计算机指纹识别技术[1]是一门综合性的技术,21世纪的今天,它已成为可靠的个人身份鉴定的方法之一.在所有生物识别技术中,指纹识别技术是应用最广泛最普及的,例如它可以应用于金融、保险、证券行业的身份认证,安防业,人力资源管理等等.Fingerprint recognition is an active subject in the field of pattern recognition which has an extensive applied foreground. People are more and more concerned about how to classify and how to store the huge number of fingerprint template information. The paper presents a classifiable algorithm of fingerprint template based on BP neural networks. Having simply introducing the process of image precondition and fingerprint template building, we emphatically formulate a self-adapting and step-changing algorithm used gold-segmentation. At last,the simulation result indicates that the new algorithm is more superior in convergent rate and precision than that of other traditional algorithms.

关 键 词：指纹模板分类器 分类算法 图像匹配算法 BP神经网络 图像识别 计算机 指纹识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] D91[自动化与计算机技术—计算机科学与技术]