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Title: Fractal and fingerprint analysis through phase embedded diffraction pattern Authors: ID Swapna, Mohanachandran Nair Sindhu, UNIVERSITY OF KERALA (Author), et al. Files: This document has no files that are freely available to the public. This document may have a physical copy in the library of the organization, check the status via COBISS.  Language: English Work type: Not categorized Typology: 1.01 - Original Scientific Article Organization: UNG - University of Nova Gorica Abstract: Fingerprint recognition is the most popular biometric identification method currently employed in security applications. Though there are several optical methods for fingerprint analysis based on intensity recording, phase recording alone can give the precise result. Interference and diffraction phenomenon are capable of recording phase variations. In the present method diffraction patterns corresponding to the fingerprints are generated and the spacing between the ridges is calculated. The spacing between ridges is found to be in agreement with the value measured using the software ImageJ. The fingerprint impressions of more than thirty-five persons are recorded and analyzed using the statistical tools in Matlab.The fingerprints are also subjected to fractal analysis. The program could successfully identify a fingerprint from the database. The present work is the first report of fingerprint analysis from diffraction pattern Keywords: Diffraction, Skew, Kurtosis, Fractals Publication version: Version of Record Year of publishing: 2017 Number of pages: 5 Numbering: 9, 8 PID: 20.500.12556/RUNG-7434  COBISS.SI-ID: 113397251  NUK URN: URN:SI:UNG:REP:HJVYF8WF Publication date in RUNG: 30.06.2022 Views: 1027 Downloads: 0 Metadata:     Cite this work Plain text BibTeX EndNote XML EndNote/Refer RIS ABNT ACM Ref AMA APA Chicago 17th Author-Date Harvard IEEE ISO 690 MLA Vancouver : Copy citation

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Record is a part of a journal

Title:	International Journal of Engineering Science and Technology
Year of publishing:	2017
ISSN:	0975-5462

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License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	29.06.2022

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