Principal axis and crease detection for slap fingerprint segmentation

Author

Zhang, Yong-Liang ; Li, Yan-Miao ; Wu, Hong-Tao ; Huang, Ya-ping ; Xiao, Gang ; Gao, Fei

Author_Institution

Inst. of Graphical & Image Process., Zhejiang Univ. of Technol., Hangzhou, China

fYear

2010

fDate

26-29 Sept. 2010

Firstpage

3081

Lastpage

3084

Abstract

In slap fingerprint segmentation, crease is the most difficult edge to correctly detect. In this paper, we present a novel yet simple and accurate algorithm for the principal axis and crease detection. Firstly, the principal axis of each foreground region is detected using the minimal rotational inertia; Secondly, the crease detection is done based on cost function minimization. This algorithm has been incorporated in a slap fingerprint segmentation scheme, previously developed by the authors, producing successful results.

Keywords

fingerprint identification; image segmentation; minimisation; object detection; Iminimal rotational inertia; cost function minimization; crease detection; principal axis; slap fingerprint segmentation; Algorithm design and analysis; Cost function; Fingerprint recognition; Frequency domain analysis; Image edge detection; Image segmentation; Minimization; cost function; crease; rotational inertia; segmentation; slap fingerprint;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2010 17th IEEE International Conference on

Conference_Location

Hong Kong

ISSN

1522-4880

Print_ISBN

978-1-4244-7992-4

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2010.5654266

Filename

5654266