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Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques
As fingerprint recognition systems have become increasingly adopted within a range of technology applications over the last decade, so too has their attention within emerging research. However, although this increased attention has led to an enhancement of the software and algorithms behind this rec...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256378/ http://dx.doi.org/10.1007/978-3-030-49190-1_20 |
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author | Alshammary, Miznah H. Iliopoulos, Costas S. Khan, Mujibur R. |
author_facet | Alshammary, Miznah H. Iliopoulos, Costas S. Khan, Mujibur R. |
author_sort | Alshammary, Miznah H. |
collection | PubMed |
description | As fingerprint recognition systems have become increasingly adopted within a range of technology applications over the last decade, so too has their attention within emerging research. However, although this increased attention has led to an enhancement of the software and algorithms behind this recognition process, the majority of research has still not addressed the issues of incorrect rotation or proximity between the finger and the device. Current systems assume that the direction of the imprinted finger will align with that of the target fingerprint image; this decreases the accuracy of fingerprint recognition across a variety of finger orientations and scenarios. In response to this use-case dilemma, this paper proposes a new technique of pattern matching that can account for this natural range of fingerprint orientations. This is achieved first through a preliminary stage of orientation identification, whereby the fingerprint image can be stored under multiple permutations by using approximate circular string-matching algorithms. This enables the database of images for each approximate permutation of orientation to be stored in advance. It can then be matched against the strong information of the fingerprint at its exact relative rotation of input. The improved accuracy of recognition demonstrated through the results of this study may enable the functionality of fingerprint recognition to adapt to challenging device form-factors and provide the accuracy needed for military and medical applications. |
format | Online Article Text |
id | pubmed-7256378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72563782020-05-29 Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques Alshammary, Miznah H. Iliopoulos, Costas S. Khan, Mujibur R. Artificial Intelligence Applications and Innovations. AIAI 2020 IFIP WG 12.5 International Workshops Article As fingerprint recognition systems have become increasingly adopted within a range of technology applications over the last decade, so too has their attention within emerging research. However, although this increased attention has led to an enhancement of the software and algorithms behind this recognition process, the majority of research has still not addressed the issues of incorrect rotation or proximity between the finger and the device. Current systems assume that the direction of the imprinted finger will align with that of the target fingerprint image; this decreases the accuracy of fingerprint recognition across a variety of finger orientations and scenarios. In response to this use-case dilemma, this paper proposes a new technique of pattern matching that can account for this natural range of fingerprint orientations. This is achieved first through a preliminary stage of orientation identification, whereby the fingerprint image can be stored under multiple permutations by using approximate circular string-matching algorithms. This enables the database of images for each approximate permutation of orientation to be stored in advance. It can then be matched against the strong information of the fingerprint at its exact relative rotation of input. The improved accuracy of recognition demonstrated through the results of this study may enable the functionality of fingerprint recognition to adapt to challenging device form-factors and provide the accuracy needed for military and medical applications. 2020-05-04 /pmc/articles/PMC7256378/ http://dx.doi.org/10.1007/978-3-030-49190-1_20 Text en © IFIP International Federation for Information Processing 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Alshammary, Miznah H. Iliopoulos, Costas S. Khan, Mujibur R. Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques |
title | Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques |
title_full | Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques |
title_fullStr | Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques |
title_full_unstemmed | Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques |
title_short | Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques |
title_sort | fingerprints recognition system-based on mobile device identification using circular string pattern matching techniques |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256378/ http://dx.doi.org/10.1007/978-3-030-49190-1_20 |
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