DESIGN OF NEW PARAMETERIZED TRANSFORMATION FUNCTIONS AND MULTI OBJECTIVE CRITERION FOR FINGERPRINT IMAGE ENHANCEMENT

STEPHEN M.J.; PRASAD REDDY P.V.G.D.

DESIGN OF NEW PARAMETERIZED TRANSFORMATION FUNCTIONS AND MULTI OBJECTIVE CRITERION FOR FINGERPRINT IMAGE ENHANCEMENT

STEPHEN M.J.¹*, PRASAD REDDY P.V.G.D.²
¹Department of CSE, Wellfare Institute of Science Technology & Management, Visakhapatnam- 530 027, AP, India.
²Department of CS & SE, Andhra University, Visakhapatnam- 530 003, AP, India.
* Corresponding Author : jamesstephenm@yahoo.com

Received : 06-11-2013 Accepted : 03-07-2014 Published : 31-07-2014
Volume : 3 Issue : 2 Pages : 54 - 59
Inform Sci Tech 3.2 (2014):54-59

Keywords : Image enhancement, Minutiae, Objective criterion, Optimization techniques, Transformation function
Conflict of Interest : None declared

Cite - MLA : STEPHEN M.J. and PRASAD REDDY P.V.G.D. "DESIGN OF NEW PARAMETERIZED TRANSFORMATION FUNCTIONS AND MULTI OBJECTIVE CRITERION FOR FINGERPRINT IMAGE ENHANCEMENT." Information Science and Technology 3.2 (2014):54-59.

Cite - APA : STEPHEN M.J., PRASAD REDDY P.V.G.D. (2014). DESIGN OF NEW PARAMETERIZED TRANSFORMATION FUNCTIONS AND MULTI OBJECTIVE CRITERION FOR FINGERPRINT IMAGE ENHANCEMENT. Information Science and Technology, 3 (2), 54-59.

Cite - Chicago : STEPHEN M.J. and PRASAD REDDY P.V.G.D. "DESIGN OF NEW PARAMETERIZED TRANSFORMATION FUNCTIONS AND MULTI OBJECTIVE CRITERION FOR FINGERPRINT IMAGE ENHANCEMENT." Information Science and Technology 3, no. 2 (2014):54-59.

Copyright : © 2014, STEPHEN M.J. and PRASAD REDDY P.V.G.D., Published by Bioinfo Publications. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

Abstract

Extracting minutiae features out of poor quality fingerprints is the most challenging problem and it is extremely difficult for the automated system to accurately classify poor quality fingerprints and reliably locate the minutiae in such fingerprint images. In the present work, some image enhancement techniques are employed in order to obtain reliable estimates of minutiae locations prior to minutiae extraction. For the task of image enhancement some parameterized transformation functions were designed, which use local and global information of the image. Some novel optimization techniques like Modified Teaching Learning Based Optimization (M-TLBO), Modified Harmony Search (M-HS), Particle Swarm Optimization, Simple League Championship Algorithm (SLCA) were used to control and change the parameters in each transformation function which is applied on the poor quality fingerprint images to remove noise. A multi objective criterion is proposed to evaluate the rate of enhancement at each step in the enhancement process. The proposed technique outperforms the other existing noise elimination techniques.

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