SECURE MACHINE LEARNING BASED TRANSACTION SYSTEM USING FINGERPRINT AUTHENTICATION

Nitigya Verma, Minakshi Memoria, Rajiv Kumar, Sunil Ghildiyal, Kapil Joshi, Shiv Dayal Pandey

202237 citationsDOI

Abstract

Human fingerprints have a wealth of minutiae, or minute characteristics, that can be used as identity marks for fingerprint verification. Our term project is to investigate fingerprint identification and transaction systems based on minutiae-based matching, which is widely utilized in fingerprint algorithms and methodologies. The approach taken in this project entails extracting minutiae points from fingerprint photos and then doing fingerprint matching between two fingerprints. If yes, the database is queried for additional information, and the information is displayed as validated. In this instance, we'll have to deal with the user's requirements. This project was created using Visual Studio.

Topics & Concepts

MinutiaeFingerprint (computing)Computer scienceFingerprint recognitionFingerprint Verification CompetitionMatching (statistics)Authentication (law)Database transactionIdentity (music)Artificial intelligenceBiometricsIdentification (biology)Information retrievalPattern recognition (psychology)Data miningComputer visionDatabaseComputer securityMathematicsBiologyAcousticsStatisticsBotanyPhysicsAdvanced Steganography and Watermarking TechniquesBiometric Identification and SecurityUser Authentication and Security Systems