Finger-vein matching based on adaptive vector field estimation

Author

Jinfeng Yang ; Meijing Wu ; Wanyin Wang ; Yihua Shi

Author_Institution

Tianjin Key Lab. for Adv. Signal Process., Civil Aviation Univ. of China, Tianjin, China

fYear

2012

fDate

Sept. 30 2012-Oct. 3 2012

Firstpage

145

Lastpage

148

Abstract

In this paper, a new finger-vein vector field estimation method is proposed for the primitive finger-vein feature representation. First, a set of spatial curve filters (SCFs) is built based on a variable curve model in curvature and orientation. To make SCFs adaptive to vein-width variations, a curve length field (CLF) estimation method is then proposed. Next, with the CLF constrain, a vein vector field is established for finger-vein feature description. Finally, finger-vein matching performance is evaluated using Phase-Only-Correlation (POC) measure. Experimental results show that the proposed method is highly powerful in improving finger-vein matching accuracy.

Keywords

curve fitting; filtering theory; fingerprint identification; image matching; image representation; CLF constraint; CLF estimation method; POC measure; SCF; adaptive vector field estimation method; curve length field estimation method; finger-vein matching; finger-vein matching accuracy; phase-only-correlation measure; primitive finger-vein feature representation; spatial curve filter; variable curve model; vein-width variation; Abstracts; Accuracy; Estimation; Feature extraction; Magnetic resonance; Vectors; Biometrics; curve filter; finger-vein matching; vector field;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2012 19th IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1522-4880

Print_ISBN

978-1-4673-2534-9

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2012.6466816

Filename

6466816