An accurate fingerprint reference point determination method based on curvature estimation of separated ridges

This paper presents an effective method for the detection of a fingerprint’s reference point by analyzing fingerprint ridges’ curvatures. The proposed approach is a multi-stage system. The first step extracts the fingerprint ridges from an image and transforms them into chains of discrete points. In...

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Main Authors: Doroz Rafal, Wrobel Krzysztof, Porwik Piotr
Format: Article
Language:English
Published: Sciendo 2018-03-01
Series:International Journal of Applied Mathematics and Computer Science
Subjects:
Online Access:https://doi.org/10.2478/amcs-2018-0016
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spelling doaj-61123188271c4f15bdcad9cf7e48e5882021-09-06T19:41:08ZengSciendoInternational Journal of Applied Mathematics and Computer Science2083-84922018-03-0128120922510.2478/amcs-2018-0016amcs-2018-0016An accurate fingerprint reference point determination method based on curvature estimation of separated ridgesDoroz Rafal0Wrobel Krzysztof1Porwik Piotr2Institute of Computer Science University of Silesia, ul. Będzinska 39, 41-200 Sosnowiec, PolandInstitute of Computer Science University of Silesia, ul. Będzinska 39, 41-200 Sosnowiec, PolandInstitute of Computer Science University of Silesia, ul. Będzinska 39, 41-200 Sosnowiec, PolandThis paper presents an effective method for the detection of a fingerprint’s reference point by analyzing fingerprint ridges’ curvatures. The proposed approach is a multi-stage system. The first step extracts the fingerprint ridges from an image and transforms them into chains of discrete points. In the second step, the obtained chains of points are processed by a dedicated algorithm to detect corners and other points of highest curvature on their planar surface. In a series of experiments we demonstrate that the proposed method based on this algorithm allows effective determination of fingerprint reference points. Furthermore, the proposed method is relatively simple and achieves better results when compared with the approaches known from the literature. The reference point detection experiments were conducted using publicly available fingerprint databases FVC2000, FVC2002, FVC2004 and NISThttps://doi.org/10.2478/amcs-2018-0016biometricsimage processingfingerprint recognitionkolmogorov-smirnov statistical testreference point
collection DOAJ
language English
format Article
sources DOAJ
author Doroz Rafal
Wrobel Krzysztof
Porwik Piotr
spellingShingle Doroz Rafal
Wrobel Krzysztof
Porwik Piotr
An accurate fingerprint reference point determination method based on curvature estimation of separated ridges
International Journal of Applied Mathematics and Computer Science
biometrics
image processing
fingerprint recognition
kolmogorov-smirnov statistical test
reference point
author_facet Doroz Rafal
Wrobel Krzysztof
Porwik Piotr
author_sort Doroz Rafal
title An accurate fingerprint reference point determination method based on curvature estimation of separated ridges
title_short An accurate fingerprint reference point determination method based on curvature estimation of separated ridges
title_full An accurate fingerprint reference point determination method based on curvature estimation of separated ridges
title_fullStr An accurate fingerprint reference point determination method based on curvature estimation of separated ridges
title_full_unstemmed An accurate fingerprint reference point determination method based on curvature estimation of separated ridges
title_sort accurate fingerprint reference point determination method based on curvature estimation of separated ridges
publisher Sciendo
series International Journal of Applied Mathematics and Computer Science
issn 2083-8492
publishDate 2018-03-01
description This paper presents an effective method for the detection of a fingerprint’s reference point by analyzing fingerprint ridges’ curvatures. The proposed approach is a multi-stage system. The first step extracts the fingerprint ridges from an image and transforms them into chains of discrete points. In the second step, the obtained chains of points are processed by a dedicated algorithm to detect corners and other points of highest curvature on their planar surface. In a series of experiments we demonstrate that the proposed method based on this algorithm allows effective determination of fingerprint reference points. Furthermore, the proposed method is relatively simple and achieves better results when compared with the approaches known from the literature. The reference point detection experiments were conducted using publicly available fingerprint databases FVC2000, FVC2002, FVC2004 and NIST
topic biometrics
image processing
fingerprint recognition
kolmogorov-smirnov statistical test
reference point
url https://doi.org/10.2478/amcs-2018-0016
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