Authentication of Biometric System using Fingerprint Recognition with Euclidean Distance and Neural Network Classifier
K. Martin Sagayam1, D. Narain Ponraj2, Jenkin Winston3, Yaspy J C4, Esther Jeba D5, Antony Clara6
1K.Martin Sagayam, Department of ECE, Karunya University, Coimbatore (Tamil Nadu), India.
2D.Narain Ponraj, Department of ECE, Karunya University, Coimbatore (Tamil Nadu), India.
3Jenkin Winston, Department of ECE, Karunya University, Coimbatore (Tamil Nadu), India.
4Yaspy J C, Department of ECE, Karunya University, Coimbatore (Tamil Nadu), India.
4Esther Jeba D, Department of ECE, Karunya University, Coimbatore (Tamil Nadu), India.
5Antony Clara, Department of ECE, Karunya University, Coimbatore (Tamil Nadu), India.
Manuscript received on 05 February 2019 | Revised Manuscript received on 13 February 2019 | Manuscript published on 28 February 2019 | PP: 766-771 | Volume-8 Issue-4, February 2019 | Retrieval Number: D2796028419/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays, Fingerprint recognition is the one of the authentication used for security applications. It provides hope for the society in reliable authentic biometric systems. Fingerprint technology emerges in various sectors such as government, organizations, libraries, universities, banks etc. It is widely used for biometric systems other than Iris, Face, Hand, Voice and Signature because of its uniqueness and distinctness. Traditional methods are not effectively used for analyzing the texture feature of finger print than neural network classifier. Fingerprint recognition will be identified and classified with the help of Euclidean distance and NN classifier for better accuracy has proposed in this paper. It uses certain techniques in preprocessing the image such as Histogram equalization and Fast Fourier transform. The performance of the proposed approach has significant result than the existing techniques used in the finger print recognition system.
Keyword: Euclidean Distance, Fingerprint Recognition, NN Classifier.
Scope of the Article: Pattern Recognition