z-logo
open-access-imgOpen Access
A Machine Learning Approach for Enhanced Fingerprint Recognition Technique
Author(s) -
Heli Shah,
Rajat Arora
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017915627
Subject(s) - computer science , fingerprint (computing) , artificial intelligence , machine learning , pattern recognition (psychology)
With the increasing awareness about the security systems, there has been a development of different types of biometric systems in this field. One of the most common and cost effective biometric systems is Fingerprint Biometrics. Enhanced Fingerprint Identification Technique describes mathematical algorithms to overcome the limitations faced while using the conventional fingerprint biometric systems. Enhanced Fingerprint Identification Technique provides improvised and efficient recognition process. Lumidigm sensor, captures images of skin at different wavelengths, has been used to get a multispectral image of fingerprint. GLCM algorithm is used for extracting features from the acquired fingerprint image. DTW Comparison is used for identification and verification process. Machine learning based amalgamated algorithms will overcome the hindrance faced in the recognition process while using the conventional fingerprint scanner.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom