In-Depth Examination of a Fingerprint Recognition System Using the Gabor Filter

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.