Fingerprint minutiae matching using the adjacent feature vector

被引：21

作者：

Tong, XF ^{[1
]}

Huang, JH

Tang, XL

Shi, DM

机构：

[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China

[2] Daqing Petr Inst, Daqing, Peoples R China

[3] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore

来源：

PATTERN RECOGNITION LETTERS | 2005年 / 26卷 / 09期

基金：

中国国家自然科学基金;

关键词：

fingerprint verification; minutiae matching; adjacent feature vector;

D O I：

10.1016/j.patrec.2004.11.012

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Minutiae matching is the most popular approach to fingerprint verification. In this paper, we propose a novel fingerprint feature named the adjacent feature vector (AFV) for fingerprint matching. An AFV consists of four adjacent relative orientations and six ridge counts of a minutia. Given a fingerprint image, the optimal matching score is computed in three stages: (1) minutiae candidate pairs searching based on AFVs; (2) coordinate transform for image rotation and translation; and (3) transformed minutiae matching to get matching score. The experimental results show that the proposed method provides a good trade-off between speed and accuracy. (c) 2004 Elsevier B.V. All rights reserved.

引用

页码：1337 / 1345

页数：9

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