Analysis of Fingerprint Recognition System Using Neural Network

Abstract

Fingerprint identification has a substantial efficacy in forensic science and aids criminal investigations. Fingerprints are distinctive and remain enduring throughout a person’s life. The automatic fingerprint recognition systems are based on ridges and their characteristics known as minutiae. Hence it is extremely important to mark these minutiae accurately and reject the false ones. In this work, we have used ridge termination and ridge bifurcation as minutiae for fingerprint recognition systems. At the time of the analysis of algorithms, the approaches of attributes impart better results. The recognition rate is increased & the error rate diminishes with the aid of this technique. The most important step here in automatic fingerprint matching is to securely extract the minutiae from the captured fingerprint binary images. There are already a variety of techniques are available for extracting fingerprint minutiae. The recognition rate of this intended method of fingerprint recognition system using neural networks is 91.10%. From the extricate outcome, we may infer about a very affirmative impact of neural networks on the comprehensive recognition rate, specifically in low excellence images.

Keywords: Fingerprints, Feature Extraction, Matching, Neural Network

JEL Classification: C00,L15