FINGERPRINT IDENTIFICATION A Support Vector Machine Approach

被引：0
|
作者：
Kristensen, Terje [1 ]
机构：
[1] Bergen Univ Coll, Dept Comp Engn, Nygardsgaten 112, N-5020 Bergen, Norway
来源：
ICAART 2010: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1: ARTIFICIAL INTELLIGENCE | 2010年
关键词：
AFIS; SVM; Classification rate;
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：
In this work a hybrid technique for classification of fingerprint identification has been developed to decrease the matching time. For classification a Support Vector Machine is described and used. Automatic Fingerprint Identification Systems are widely used today, and it is therefore necessary to find a classification system that is less time-consuming. The given fingerprint database is decomposed into four different subclasses and a SVM algorithm is used to train the system to do correct classification. The classification rate has been estimated to about 87.0 % of unseen fingerprints. The average matching time is decreased with a factor of about 3.5 compared to brute force search applied.
引用
收藏
页码：451 / 458
页数：8
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