Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach
International Journal of Mineral Processing and Extractive Metallurgy
Volume 2, Issue 2, March 2017, Pages: 13-20
Received: May 17, 2017; Accepted: Jun. 12, 2017; Published: Jul. 25, 2017
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Authors
Komal Kashyap, Department of Electronics & Telecommunication Engineering, Bhilai Institute of Technology Durg, Chhattisgarh, India
Ekta Tamrakar, Department of Electronics & Telecommunication Engineering, Bhilai Institute of Technology Durg, Chhattisgarh, India
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Abstract
The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox.
Keywords
Biometrics, Multibiometrics, Left and Right Palmprint Image, Feature Extraction, Discrete Wavelet Packet Transform (DWPT)
To cite this article
Komal Kashyap, Ekta Tamrakar, Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach, International Journal of Mineral Processing and Extractive Metallurgy. Vol. 2, No. 2, 2017, pp. 13-20. doi: 10.11648/j.ijmpem.20170202.11
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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