Fingerprint Individuality Model Based on Pattern Type and Singular Point Attributes

Year 2021, Volume: 10 Issue: 3, 75 - 85, 01.09.2021

Gabriel Babatunde Iwasokun Oluwatayo Samuel Ogunlana Olatubosun Olabode

Abstract

This paper presents a singular point and pattern type model for the investigation of fingerprint individuality. The extraction of the singular point is based on the modified Poincare method while the determination of the pattern type is based on plane geometry and the attributes of the singular point on the quadrants. The experimental study of the platform was carried out on a Microsoft Windows 10 Professional platform on HP Pavilion Core i7 with 8.00GB RAM and 750 GB Hard Disk. Matlab version R2018a was the frontend while Microsoft Access Relational Database Management System served the backend. Benchmarked FVC2002 fingerprint database which comprises four datasets from different sources and of varied types served as experimental dataset. The experimental study established the viability and the functionality of the model while results for average matching time, false non match rate and false match rate confirmed that the model is practically feasible as well as its suitability for use in Automated Fingerprint Identification System AFIS .

Keywords

Fingerprint, singular point, pattern type, FVC2002, individuality

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