Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification

<p/> <p>Most of the proposed methods used for fingerprint verification are based on local visible features called <it>minutiae</it>. However, due to problems for extracting minutiae from low-quality fingerprint images, other discriminatory information has been considered. In...

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Main Authors: Helfroush Sadegh, Ghassemian Hassan
Format: Article
Language:English
Published: SpringerOpen 2007-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://asp.eurasipjournals.com/content/2007/060590
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spelling doaj-e6565010da2347599c726334f6617ebe2020-11-25T01:01:29ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802007-01-0120071060590Nonminutiae-Based Decision-Level Fusion for Fingerprint VerificationHelfroush SadeghGhassemian Hassan<p/> <p>Most of the proposed methods used for fingerprint verification are based on local visible features called <it>minutiae</it>. However, due to problems for extracting minutiae from low-quality fingerprint images, other discriminatory information has been considered. In this paper, the idea of decision-level fusion of <it>orientation</it>, <it>texture,</it> and <it>spectral</it> features of fingerprint image is proposed. At first, a value is assigned to the similarity of block orientation field of two-fingerprint images. This is also performed for texture and spectral features. Each one of the proposed similarity measure does not need core-point existence and detection. Rotation and translation of two fingerprint images are also taken into account in each method and all points of fingerprint image are employed in feature extraction. Then, the similarity of each feature is normalized and used for decision-level fusion of fingerprint information. The experimental results on <it>FVC2000</it> database demonstrate the effectiveness of the proposed fusion method and its significant accuracy.</p> http://asp.eurasipjournals.com/content/2007/060590
collection DOAJ
language English
format Article
sources DOAJ
author Helfroush Sadegh
Ghassemian Hassan
spellingShingle Helfroush Sadegh
Ghassemian Hassan
Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification
EURASIP Journal on Advances in Signal Processing
author_facet Helfroush Sadegh
Ghassemian Hassan
author_sort Helfroush Sadegh
title Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification
title_short Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification
title_full Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification
title_fullStr Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification
title_full_unstemmed Nonminutiae-Based Decision-Level Fusion for Fingerprint Verification
title_sort nonminutiae-based decision-level fusion for fingerprint verification
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2007-01-01
description <p/> <p>Most of the proposed methods used for fingerprint verification are based on local visible features called <it>minutiae</it>. However, due to problems for extracting minutiae from low-quality fingerprint images, other discriminatory information has been considered. In this paper, the idea of decision-level fusion of <it>orientation</it>, <it>texture,</it> and <it>spectral</it> features of fingerprint image is proposed. At first, a value is assigned to the similarity of block orientation field of two-fingerprint images. This is also performed for texture and spectral features. Each one of the proposed similarity measure does not need core-point existence and detection. Rotation and translation of two fingerprint images are also taken into account in each method and all points of fingerprint image are employed in feature extraction. Then, the similarity of each feature is normalized and used for decision-level fusion of fingerprint information. The experimental results on <it>FVC2000</it> database demonstrate the effectiveness of the proposed fusion method and its significant accuracy.</p>
url http://asp.eurasipjournals.com/content/2007/060590
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