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Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques

by Vidaydevi G. Biradar, Sarojadevi H.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 3
Year of Publication: 2014
Authors: Vidaydevi G. Biradar, Sarojadevi H.
10.5120/15859-4773

Vidaydevi G. Biradar, Sarojadevi H. . Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques. International Journal of Computer Applications. 91, 3 ( April 2014), 8-13. DOI=10.5120/15859-4773

@article{ 10.5120/15859-4773,
author = { Vidaydevi G. Biradar, Sarojadevi H. },
title = { Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 3 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number3/15859-4773/ },
doi = { 10.5120/15859-4773 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:11:47.304602+05:30
%A Vidaydevi G. Biradar
%A Sarojadevi H.
%T Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 3
%P 8-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Personal identification based on fingerprints is very popular compared to identification based on other biometric features like iris, gait and face etc. Performance of automatic fingerprints identification systems depends upon the quality of fingerprints. Extraction of fingerprints features in poor quality fingerprints is challenging task. Accurate measurement of fingerprints feature improves the accuracy of identification systems. Fingerprints consists of ridge and valley structures and offers different types of features, they are categorized as level 1, level 2 and level 3 features. Level 1 features are singular points which are used for fingerprints registration, classification etc. Level 2 features are ridge features like minutiae points, ridge orientation etc. , and commercially available fingerprint recognition systems are based on level 2 features. Level 3 features include sweat pores, incipient ridges etc. Among these features ridge orientation is used for fingerprint enhancement, fingerprint classification, indexing and fingerprint segmentation. This paper provides an overview of existing state of the art techniques for ridge orientation estimation.

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Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint recognition Ridge orientation combinational model Latent Gradients Singular points.

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