Palm Vein Technology for Biometrics
Charu Jain1, Ved Mishra2, Aarti Chugh3
1Dr. Charu Jain, Amity School of Engineering and Technology, Amity University, Gurgaon, India.
2Dr. Ved Mishra, Amity School of Engineering and Technology, Amity University, Gurgaon, India.
3Aarti Chugh, Amity School of Engineering and Technology, Amity University, Gurgaon, India.
Manuscript received on 05 August 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 26 August 2019 | PP: 598-602 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10940789S19/19©BEIESP | DOI: 10.35940/ijitee.I1094.0789S19
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© 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: The use and implementation of biometrics for identification and authentication has become more important in the past decade. This is because there has been an increased risk associated with textual passwords such as dictionary attacks, eavesdropping, shoulder surfing etc. We have worked on Palm vein recognition for detecting palm veins in applications for biometric security using near infrared absorption phenomena. The goal is to produce a software prototype that is capable of identifying a person by the vein structures of the hand. The images used for the same were taken from the CASIA-MS-PalmprintV1 database collected by the Chinese Academy of Sciences’ Institute of Automation (CASIA). After pre-processing, LDR and DCT have been used for feature extraction and Euclidian Distance is calculated for generating matching score. Acceptance/rejection is based on this matching score. The efficiency obtained was 93.2% when compared with other systems.
Keywords: Voice Recognition System, Fuzzy Logic, Genetic Algorithm, Age Based Voice Classification, Support Vector Machine(SVM), Gaussian Mixture Model(GMM)
Scope of the Article: Autonomic Computing and Agent-Based Systems