Fingerprint Recognition using Deep Convolutional Network and Machine Learning

Abstract

This research investigates the application of Deep Convolutional Networks (DCNs) and machine learning techniques in the realm of fingerprint recognition. Fingerprint identification is a critical aspect of biometric security, and the study aims to enhance accuracy and efficiency by harnessing the power of DCNs. The research involves the development of a robust model for fingerprint feature extraction, leveraging convolutional layers for spatial hierarchies. Through comprehensive experimentation and evaluation, the study endeavours to contribute to advancements in biometric authentication systems, addressing challenges such as variability in fingerprint patterns and ensuring robust performance across diverse datasets.