Fingerprint Singular Point Detection Based on Multiple-Scale Orientation Entropy

被引：10

作者：

Chen, Hongtao ^{[1
]}

Pang, Liaojun ^{[1
]}

Liang, Jimin ^{[1
]}

Liu, Eryun ^{[1
]}

Tian, Jie ^{[1
,2
]}

机构：

[1] Xidian Univ, Sch Life Sci & Technol, Xian 710071, Peoples R China

[2] Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China

来源：

IEEE SIGNAL PROCESSING LETTERS | 2011年 / 18卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Entropy; multiple-scale analysis; orientation field; orientation field flow curve; singular point detection; ALGORITHM; MODEL;

D O I：

10.1109/LSP.2011.2169957

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This letter develops a novel method for fingerprint singular point detection based on a new singularity representation of ridge-valley region called orientation entropy. The candidate singular point is obtained by the multiple-scale analysis of orientation entropy and some post processing steps are proposed to filter the spurious core and delta points. An iteration compensation scheme is proposed to search the precise location for core points against the offset further. Performance of the proposed method has been evaluated on the dataset of FVC2002 DB1. Experimental results show that the multiple-scale orientation entropy is correct and effective for singular detection and the location compensation scheme reduces the distance between the detection result and the truth singular point.

引用

页码：679 / 682

页数：4

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