An IoT Enabled Finger-Vein Recognition System in Mobile Devices for Atm Users
R Gnanaselvam1, M S Vasanthi2
1R Gnanaselvam, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, (Tamil Nadu), India.
2M S Vasanthi, Associate Professor, Department of Telecommunication, SRM Institute of Science and Technology, (Tamil Nadu), India.
Manuscript received on 02 April 2019 | Revised Manuscript received on 18 April 2019 | Manuscript Published on 30 April 2019 | PP: 41-46 | Volume-7 Issue-6S6 April 2019 | Retrieval Number: F10090476S619/2019©BEIESP | DOI: 10.35940/ijrte.F1009.0476S619
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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: In existing protection system such as PIN(Personal Identification Number), Finger Print, Palm Print, Face Recognition, Iris recognition systems for ATM(Automated Teller Machine) users have more complicated and also these systems data’s will be hacked from other users easily. So in order to over come such problems, we go for finger vein recognition system. Here finger vein means we can take a finer vein image from inner structure of finger using NIR (Near Infrared) camera, but in this paper, we can take a set of sample finger vein images and stored in the data base from different users and compared with current user image using Euclidean distance algorithm. If the database and user images are equal then we can execute the transaction from ATM suppose if these two images are mismatched then we can not able to execute the transaction from ATM and also we can transfer the information to the police as well as corresponding customer such as “Unauthorized person using your account” through mobile phone using GSM (Global System for Mobile) and NODE MCU to the process the data’s using IoT (Internet of things).
Keywords: Finger-vein Recognition; Biometrics; Mobile Devices; NODE MCU; Internet of Things, GSM.
Scope of the Article: Pattern Recognition