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Research Article Open access CC BY 3.0

Review and Evaluation of Fingerprint Singular Point Detection Algorithms

Gabriel Babatunde Iwasokun, Sunday Olusegun Ojo

Current Journal of Applied Science and Technology · pp. 4918–4938 · Published 30 Sep 2014

10.9734/BJAST/2014/12218

Abstract

Fingerprint has continued to enjoy dominance over other biometrics like face, iris, nose, signature among others in human verification and authentication. This is promoted by its major characteristics which include availability, uniqueness, consistency and reliability. Fingerprint verification and authentication involves the serial stages of enrolment, processing and matching. Enrolment through a number of fingerprint capturing devices helps to read the fingerprint into a target location from where processing takes place. Processing of a fingerprint image involves enhancement, feature extraction and singular point detection. Matching of fingerprint is performed based on the extraction results to establish its source or similarity level. The extraction of true singular (core and delta) and feature points is paramount for a true fingerprint matching and a number of algorithms had been formulated to accomplish it. This paper presents a review and evaluation of commonly known fingerprint singular point detection algorithms with emphasis on methodologies, strengths and weaknesses.

Fingerprint singular point core and delta Poincare orientation field geometry of region

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