Vector Quantization and multi class Support Vector Machines based fingerprint classification

被引：0

作者：

Choudhury, Sabarna ^{[1
]}

Bandyopadhyay, Shreyasi ^{[1
]}

Mukhopadhyay, Sayan ^{[1
]}

Mukherjee, Subhajit ^{[1
]}

机构：

[1] St Thomas Coll Engn & Technol, Elect & Commun Engn, Kolkata, India

来源：

2016 INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT), VOL 2 | 2016年

关键词：

fingerprint recognition; vector quantization; Linde Buzo Gray algorithm; multi class Support Vector Machines; comaparator technique;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Fingerprint recognition, one of the important biometric verification tools plays an important role in maintaining good security in any sort of systems. The fingerprint recognition in this paper deals with the extraction of features followed by codebook formation by Linde Buzo Gray Vector Quantization. The system also adds a sophisticated multi class Support Vector Machine classifier with a comparator technique which enhances the efficacy of the system. The classifier obtains an overall accuracy of 94% fingerprint verification with no rejects.

引用

页码：7 / 10

页数：4

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