A Study on Fingerprint Hash Code Generation Using Euclidean Distance for Identifying a User

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Bibliographic Details
Title: A Study on Fingerprint Hash Code Generation Using Euclidean Distance for Identifying a User
Authors: Sreeramana Aithal P., orcid:0000-0002-4691-, Krishna Prasad, K.
Publisher Information: Zenodo
Publication Year: 2017
Collection: Zenodo
Subject Terms: Fingerprint image, Fingerprint hashcode, Authentication, Multifactor authentication model, Euclidean distance
Description: Biometrics innovation has ended up being a precise and proficient response to the security issue. Biometrics is a developing field of research as of late and has been dedicated to the distinguishing proof or authentication of people utilizing one or multiple inherent physical or behavioural characteristics. The unique fingerprint traits of a man are exceptionally exact and are special to a person. Authentication frameworks in light of unique fingerprints have demonstrated to create low false acceptance rate and false rejection rate, alongside other favourable circumstances like simple and easy usage strategy. But the modern study reveals that fingerprint is not so secured like secured passwords which consist of alphanumeric characters, number and special characters. Fingerprints are left at crime places, on materials or at the door which is usually class of latent fingerprints. We cannot keep fingerprint as secure like rigid passwords. In this paper, we discuss fingerprint image Hash code generation based on the Euclidean distance calculated on the binary image. Euclidean distance on a binary image is the distance from every pixel to the nearest neighbour pixel which is having bit value one. Hashcode alone not sufficient for Verification or Authentication purpose, but can work along with Multifactor security model or it is half secured. To implement Hash code generation we use MATLAB2015a. This study shows how fingerprints Hash code uniquely identifies a user or acts as index-key or identity-key.
Document Type: article in journal/newspaper
Language: unknown
Relation: https://zenodo.org/records/1133545; oai:zenodo.org:1133545; https://doi.org/10.5281/zenodo.1133545
DOI: 10.5281/zenodo.1133545
Availability: https://doi.org/10.5281/zenodo.1133545
https://zenodo.org/records/1133545
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number: edsbas.5A47FE5A
Database: BASE
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