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
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;
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
DOI :
10.1109/ISCSCT.2008.122