Performance Analysis and Designing of Technique for Enhancement of Fingerprints based on the Estimated Local Ridge Orientation and Frequency
Virender Kadyan1, Ritu Aggarwal2

1Prof. Virender Kadyan CSE Department, Kurukshetra University/ SGI College, Samalkha, INDIA.
2Ritu Aggarwal, CSE Department, Kurukshetra university/ SGI College, Samalkha, INDIA.
Manuscript received on June 25, 2014. | Revised Manuscript received on July 03, 2014. | Manuscript published on July 05, 2014. | PP: 50-53 | Volume-4, Issue-3, July 2014. | Retrieval Number: C2286074314/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Fingerprint identification is a growing and popular biometric identification technology. It includes two steps one is fingerprint verification and other is fingerprint recognition. Both of them use minutiae, such as end points and bifurcation points, as features. Therefore, how to appropriately extract minutiae from fingerprint images becomes an important step in fingerprint identification. Extracting features from fingerprints is an essential step in fingerprint verification and recognition. Many algorithms for this issue have been developed recently. on. The goal of this paper is to develop a system that can be used for fingerprint verification through extracting and matching minutiae. To achieve good minutiae, initially, extraction is done in fingerprints with varying quality, then preprocessing in form of image enhancement. Many methods have been joined to build a minutia extractor and a minutia matcher. A fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency, is be implemented in this paper. Performance of the new developed system is then evaluated using visual analysis and goodness index value of enhanced image. 
Keywords: Enhancement, Fingerprint, Ridges, Valleys