DocumentCode
2098000
Title
An Improved Fingerprint Singular Point Detection Algorithm Based on Continuous Orientation Field
Author
Tang, Ting ; Wu, Xiaopei ; Xiang, Ming
Author_Institution
Key Lab. of Intell. Comput. & Signal Process., Anhui Univ., Hefei, China
Volume
2
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
454
Lastpage
457
Abstract
It is very important to detect singular points (core and delta) accurately and reliably for classification and matching of fingerprint. In this paper, an improved method for singularity detection in fingerprint images, which based on continuous orientation field, is proposed to improve accuracy of the position and reliability of the singularity. Firstly, the blocks which may contain singularities are detected by computing the Poincare Index. Then, the singularities are detected in the block images. Experiment show that the proposed method can overcome the shortcoming of the traditional method to great extend and is robust to poor quality images.
Keywords
fingerprint identification; image classification; image matching; object detection; block image; continuous orientation field; fingerprint image classification; fingerprint image matching; fingerprint singular point detection algorithm; poincare index; Computational intelligence; Computer science; Detection algorithms; Fingerprint recognition; Gray-scale; Image matching; Image segmentation; Laboratories; Pixel; Signal processing algorithms; Poincaré Index; fingerprint classification; orientation field; singular point;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-3746-7
Type
conf
DOI
10.1109/ISCSCT.2008.122
Filename
4731662
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