Automatic Fingerprint Identification System using fuzzy Neural Techniques

被引：0
|
作者：
Mohamed, SM [1 ]
Nyongesa, HO [1 ]
Siddiqi, J [1 ]
机构：
[1] Sheffield Hallam Univ, Sch Comp & Management Sci, Ctr Res Comp, Sheffield S1 1WB, S Yorkshire, England
来源：
IC-AI'2000: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 1-III | 2000年
关键词：
fingerprint; biometrics; features encoding; matching; fuzzy neural learning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The successful use of the fingerprint identification has been employed in law enforcement for many years ago. Fingerprint technology, is one of the most mature biometrics technologies. Biometrics identification deals with identification of individuals based on their biological or behavioral characteristics (so-called positive personal identification). However, manual fingerprint identification system is so tedious, lime consuming and incapable of meeting today's increasing performance requirements. A goon performance of the Automatic Fingerprint Identification System (AFIS) highly demands. In this paper we described the AFIS which allows variations on the basic feature properties extracted from the fingerprint image for a match, then,we used fuzzy neural networks learning techniques for testing and training these features. Relative performance of AFIS and the Eye Iris Recognition among the other. Biometrics items, is examined by using issues as FRR, FTA, and FAR.
引用
收藏
页码：859 / 865
页数：7
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