Improved Fingerprint Matching by Distortion Removal

Andrew W. SENIOR; Ruud M. BOLLE

Improved Fingerprint Matching by Distortion Removal

Andrew W. SENIOR, Ruud M. BOLLE

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Fingerprint recognition is a well-researched problem, and there are several highly accurate systems commercially available. However, this biometric technology still suffers from problems with the handling of bad quality prints. Recent research has begun to tackle the problems of poor quality data. This paper takes a new approach to one problem besetting fingerprints--that of distortion. Previous attempts have been made to ensure that acquired prints are not distorted, but the novel approach presented here corrects distortions in fingerprints that have already been acquired. This correction is a completely automatic and unsupervised operation. The distortion modelling and correction are explained, and results are presented demonstrating significant improvements in matching accuracy through the application of the technique.

Publication: IEICE TRANSACTIONS on Information Vol.E84-D No.7 pp.825-832

Publication Date: 2001/07/01

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Type of Manuscript: Special Section PAPER (Special Issue on Biometric Person Authentication)

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Andrew W. SENIOR, Ruud M. BOLLE, "Improved Fingerprint Matching by Distortion Removal" in IEICE TRANSACTIONS on Information, vol. E84-D, no. 7, pp. 825-832, July 2001, doi: .
Abstract: Fingerprint recognition is a well-researched problem, and there are several highly accurate systems commercially available. However, this biometric technology still suffers from problems with the handling of bad quality prints. Recent research has begun to tackle the problems of poor quality data. This paper takes a new approach to one problem besetting fingerprints--that of distortion. Previous attempts have been made to ensure that acquired prints are not distorted, but the novel approach presented here corrects distortions in fingerprints that have already been acquired. This correction is a completely automatic and unsupervised operation. The distortion modelling and correction are explained, and results are presented demonstrating significant improvements in matching accuracy through the application of the technique.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_7_825/_p

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@ARTICLE{e84-d_7_825,
author={Andrew W. SENIOR, Ruud M. BOLLE, },
journal={IEICE TRANSACTIONS on Information},
title={Improved Fingerprint Matching by Distortion Removal},
year={2001},
volume={E84-D},
number={7},
pages={825-832},
abstract={Fingerprint recognition is a well-researched problem, and there are several highly accurate systems commercially available. However, this biometric technology still suffers from problems with the handling of bad quality prints. Recent research has begun to tackle the problems of poor quality data. This paper takes a new approach to one problem besetting fingerprints--that of distortion. Previous attempts have been made to ensure that acquired prints are not distorted, but the novel approach presented here corrects distortions in fingerprints that have already been acquired. This correction is a completely automatic and unsupervised operation. The distortion modelling and correction are explained, and results are presented demonstrating significant improvements in matching accuracy through the application of the technique.},
keywords={},
doi={},
ISSN={},
month={July},}

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TY - JOUR
TI - Improved Fingerprint Matching by Distortion Removal
T2 - IEICE TRANSACTIONS on Information
SP - 825
EP - 832
AU - Andrew W. SENIOR
AU - Ruud M. BOLLE
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2001
AB - Fingerprint recognition is a well-researched problem, and there are several highly accurate systems commercially available. However, this biometric technology still suffers from problems with the handling of bad quality prints. Recent research has begun to tackle the problems of poor quality data. This paper takes a new approach to one problem besetting fingerprints--that of distortion. Previous attempts have been made to ensure that acquired prints are not distorted, but the novel approach presented here corrects distortions in fingerprints that have already been acquired. This correction is a completely automatic and unsupervised operation. The distortion modelling and correction are explained, and results are presented demonstrating significant improvements in matching accuracy through the application of the technique.
ER -