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Fingerprint image enhancement using multiple filters

Biometrics is the measurement of an individual’s distinctive physical and behavioral characteristics. In comparison to traditional token-based or knowledge-based forms of identification, biometrics such as fingerprints, are more reliable. Fingerprint images recorded digitally can be affected by scan...

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Autores principales: Shams, Haroon, Jan, Tariqullah, Khalil, Amjad Ali, Ahmad, Naveed, Munir, Abid, Khalil, Ruhul Amin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280261/
https://www.ncbi.nlm.nih.gov/pubmed/37346560
http://dx.doi.org/10.7717/peerj-cs.1183
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author Shams, Haroon
Jan, Tariqullah
Khalil, Amjad Ali
Ahmad, Naveed
Munir, Abid
Khalil, Ruhul Amin
author_facet Shams, Haroon
Jan, Tariqullah
Khalil, Amjad Ali
Ahmad, Naveed
Munir, Abid
Khalil, Ruhul Amin
author_sort Shams, Haroon
collection PubMed
description Biometrics is the measurement of an individual’s distinctive physical and behavioral characteristics. In comparison to traditional token-based or knowledge-based forms of identification, biometrics such as fingerprints, are more reliable. Fingerprint images recorded digitally can be affected by scanner noise, incorrect finger pressure, condition of the finger’s skin (wet, dry, or abraded), or physical material it is scanned from. Image enhancement algorithms applied to fingerprint images remove noise elements while retaining relevant structures (ridges, valleys) and help in the detection of fingerprint features (minutiae). Amongst the most common image enhancement filters is the Gabor filter, however, given their restricted maximum bandwidth as well as limited range of spectral information, it falls short. We put forward a novel method of fingerprint image enhancement using a combination of a diffusion-coherence filter and a 2D log-Gabor filter. The log-Gabor overcomes the limitations of the Gabor filter while Coherence Diffusion mitigates noise elements within fingerprint images. Implementation is done on the FVC image database and assessed via visual comparison with coherence diffusion used disjointedly and with the Gabor filter.
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spelling pubmed-102802612023-06-21 Fingerprint image enhancement using multiple filters Shams, Haroon Jan, Tariqullah Khalil, Amjad Ali Ahmad, Naveed Munir, Abid Khalil, Ruhul Amin PeerJ Comput Sci Bioinformatics Biometrics is the measurement of an individual’s distinctive physical and behavioral characteristics. In comparison to traditional token-based or knowledge-based forms of identification, biometrics such as fingerprints, are more reliable. Fingerprint images recorded digitally can be affected by scanner noise, incorrect finger pressure, condition of the finger’s skin (wet, dry, or abraded), or physical material it is scanned from. Image enhancement algorithms applied to fingerprint images remove noise elements while retaining relevant structures (ridges, valleys) and help in the detection of fingerprint features (minutiae). Amongst the most common image enhancement filters is the Gabor filter, however, given their restricted maximum bandwidth as well as limited range of spectral information, it falls short. We put forward a novel method of fingerprint image enhancement using a combination of a diffusion-coherence filter and a 2D log-Gabor filter. The log-Gabor overcomes the limitations of the Gabor filter while Coherence Diffusion mitigates noise elements within fingerprint images. Implementation is done on the FVC image database and assessed via visual comparison with coherence diffusion used disjointedly and with the Gabor filter. PeerJ Inc. 2023-01-03 /pmc/articles/PMC10280261/ /pubmed/37346560 http://dx.doi.org/10.7717/peerj-cs.1183 Text en ©2023 Shams et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Shams, Haroon
Jan, Tariqullah
Khalil, Amjad Ali
Ahmad, Naveed
Munir, Abid
Khalil, Ruhul Amin
Fingerprint image enhancement using multiple filters
title Fingerprint image enhancement using multiple filters
title_full Fingerprint image enhancement using multiple filters
title_fullStr Fingerprint image enhancement using multiple filters
title_full_unstemmed Fingerprint image enhancement using multiple filters
title_short Fingerprint image enhancement using multiple filters
title_sort fingerprint image enhancement using multiple filters
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280261/
https://www.ncbi.nlm.nih.gov/pubmed/37346560
http://dx.doi.org/10.7717/peerj-cs.1183
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