Robust detection of singular points for fingerprint recognition

Author

Wei, Shen ; Xia, Chen ; Shen, Jun

Author_Institution

Dept. of Electron. & Commun. Eng., Zhongshan Univ., Guangzhou, China

Volume

2

fYear

2003

fDate

1-4 July 2003

Firstpage

439

Abstract

Detection of fingerprint singular points is an important and difficult task in automatic fingerprint classification and identification. In this paper, a robust method for the detection of such points is presented. An improved Poincare index, the orientation variation measure and the use of gray value variance, and combination of them are proposed for fingerprint singular point detection and positioning. Experimental results on fingerprint images and comparison with traditional methods show less computational complexity and more robustness of the method proposed.

Keywords

fingerprint identification; image classification; Poincare index; automatic fingerprint classification; automatic fingerprint identification; fingerprint images; fingerprint recognition; fingerprint singular point positioning; fingerprint singular points detection; gray value variance; Computational complexity; Fingerprint recognition; Image matching; Image recognition; Laboratories; Pixel; Position measurement; Robustness; Smoothing methods; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on

Print_ISBN

0-7803-7946-2

Type

conf

DOI

10.1109/ISSPA.2003.1224908

Filename

1224908