Title :
Singularity detection in fingerprint image using orientation consistency
Author :
Zacharias, G.C. ; Lal, P.S.
Author_Institution :
Dept. of Comput. Applic., MES Coll. of Eng., Kuttippuram, India
Abstract :
In spite of the fact that a fingerprint image may suffer from problems like noises and distortions, estimating core and delta points (singular points) is crucial for most of the automatic fingerprint identification system (AFIS). Singular points have wide range of uses in AFIS which include fingerprint alignment and classification. This paper presents a simple method to locate singular points from fingerprint images using orientation consistency measure. Since consistency of the orientation field is minimum in singular regions, this method will find the local minimum to accurately detect the singular points. Core and delta points are distinguished by using the orientation field change. Experimental results show that our proposed algorithm can detect singular points effectively.
Keywords :
distortion; fingerprint identification; image classification; image denoising; object detection; AFIS; automatic fingerprint identification system; delta points; distortions; fingerprint alignment; fingerprint classification; fingerprint image; noises; orientation consistency; singularity detection; Estimation; Feature extraction; Fingerprint recognition; Image segmentation; Noise; Reliability; Vectors; fingerprint recognition; orientation consistency; singular points;
Conference_Titel :
Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), 2013 International Multi-Conference on
Conference_Location :
Kottayam
Print_ISBN :
978-1-4673-5089-1
DOI :
10.1109/iMac4s.2013.6526398