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Fingerprints Recognition System-Based on Mobile Device Identification Using Circular String Pattern Matching Techniques

Research output: Chapter in Book/Report/Conference proceedingConference paper

Miznah H. Alshammary, Costas S. Iliopoulos, Mujibur R. Khan

Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops - MHDW 2020 and 5G-PINE 2020, Proceedings
EditorsIlias Maglogiannis, Lazaros Iliadis, Elias Pimenidis
PublisherSPRINGER
Pages225-231
Number of pages7
ISBN (Print)9783030491895
DOIs
Published1 Jan 2020
Event9th Mining Humanistic Data Workshop, MHDW 2020, and the 5th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2020, held as parallel events of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020 - Neos Marmaras, Greece
Duration: 5 Jun 20207 Jun 2020

Publication series

NameIFIP Advances in Information and Communication Technology
Volume585 IFIP
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference9th Mining Humanistic Data Workshop, MHDW 2020, and the 5th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2020, held as parallel events of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020
CountryGreece
CityNeos Marmaras
Period5/06/20207/06/2020

King's Authors

Abstract

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.

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