ISSN :2582-9793

Advancing Fingerprint Template Generation and Matching with Recast Minutiae Clustering and mRBFN

Original Research (Published On: 30-Jan-2024 )
Advancing Fingerprint Template Generation and Matching with Recast Minutiae Clustering and mRBFN

diptadip maiti, Madhuchhanda Basak and debashis das

Adv. Artif. Intell. Mach. Learn., 4 (1):1847-1865

diptadip maiti : TECHNO INDIA UNIVERSITY

Madhuchhanda Basak : techno india university

debashis das : techno india university

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Article History: Received on: 25-Nov-23, Accepted on: 23-Jan-24, Published on: 30-Jan-24

Corresponding Author: diptadip maiti

Email: diptadipmaiti@gmail.com

Citation: Diptadip maiti, Madhuchhanda Basak, Debashis Das (2024). Advancing Fingerprint Template Generation and Matching with Recast Minutiae Clustering and mRBFN. Adv. Artif. Intell. Mach. Learn., 4 (1 ):1847-1865


Abstract

    

Rapid development of automation in the day to day life activity mark up the need of securing bio-metric template and the privacy of rightful owner. Minutiae based matching is the most popular in the fingerprint recognition system, which greatly suffers from non-linear distortion like translation and rotation.  To deal with linear distortion most of the technique proposed in the literature depends upon a reference or singular point.  The paper proposes a binary template generation technique which apply an unsupervised clustering technique with out fixing the no of cluster. Instead of position and orientation of the minutiae points the cardinality of the clusters are stored and converted into binary template. No spatial pattern information about the fingerprint is stored in the template to protect it from spoofing and information leakage.  By the help of modified Radial Basis Function Network(mRBFN) with robust and efficient matching technique the generated templates are matched for authentication. We use MCYT dataset for training the mRBFN. The efficiency of the proposed scheme is evaluated on FVC 2000, FVC 2002 and FVC 2004 dataset.

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