In-Depth Examination of a Fingerprint Recognition System Using the Gabor Filter · Alnoor Digital Repository

Title: In-Depth Examination of a Fingerprint Recognition System Using the Gabor Filter
Abstract: Background: Due to the uniqueness of individual
fingerprint patterns, fingerprint recognition is a critical biometric
identifying tool. Because of its pervasiveness and dependability,
this technology requires ongoing refining and comprehension of its
core
concepts and applications in diverse real-world
circumstances.
Objective: This article aims to show how to use Gabor filters
and the Euclidean distance to extract and match features. The
system aims to explain the fundamental ideas of fingerprint
recognition and show how accurate and efficient it is at identifying
people.
Methods: The system uses Gabor filters to capture fine details
in fingerprint images, producing a fixed-length finger code. The
Euclidean distance is employed to compare finger codes, making
the matching process more efficient. The suggested algorithm is
rigorously tested using the FVC2000 database, with picture quality
improvements such as Gaussian filtering and histogram
equalisation implemented.
Results: The system demonstrated its proficiency in fingerprint
identification with a significant accuracy of 98.22%. The results
highlight the system's essential character while recognising the
need for sophisticated methodologies and application adjustments.
Conclusion: While the system serves as a core model for
comprehending fingerprint identification, it emphasises the
significance of future study and development in picture
pretreatment, feature extraction methods, matching approaches,
and database administration. This article's insights contribute to
the continuous advances in biometric identification technology by
resolving problems and improving the reliability of fingerprint
recognition systems.
Scientific Type: غير معروف
Link: https://fruct.org/publications/volume-35/fruct35/
Journal volume: vol.35,no.1
Collaboration type: مشترك
Publish Date: April 26, 2024
Participated Universities (Publication): Alnoor University
Scopus status: In Scopus
Scopus index year: 2 024
Scopus citation score: 0
Clarivate status: Not In Clarivate
Pub. Med. status: Not In PubMed
Author (Publication): محمد نذير إسماعيل قاسم
Journal (Publication): PROCEEDING OF THE 35TH CONFERENCE OF FRUCT ASSOCIATION
Publisher (Publication): IEEE Computer Society
ISSN: 2305-7254
Country (Publication): Russian Federation
Country type: عالمية
College (Publication): College of Education
Departement (Publication): Department of Computer Science

Media: Academic paper