SIFT based Dorsal Vein Recognition System for Cashless Treatment through Medical Insurance
Rajendra Kumar1, Ram Chandra Singh2, Ashok Kumar Sahoo3
1Rajendra Kumar, Research Scholar, Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India.
2Ram Chandra Singh, Department of Physics, School of Basic Sciences and Research, Sharda University, Greater Noida, India.
3Ashok Kumar Sahoo, Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, India.
Manuscript received on 05 September 2019 | Revised Manuscript received on 29 September 2019 | Manuscript Published on 29 June 2020 | PP: 444-451 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J108208810S19//2019©BEIESP | DOI: 10.35940/ijitee.J1082.08810S19
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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 time has come not to carry any physical personal identity. The person’s identity will be known by his/her biometric features for any purpose exclusively when the person is unconscious and not carrying any identity proof. Vein recognition system is leading biometric trait in terms of flexibility and security. The fake recognition of veins is almost impossible as the feature points lie underneath the skin and cannot be read without the knowledge of a person (if not unconscious). Most important thing about it is that vein recognitionsystem works only in living persons. In this paper, a recognition system is proposed that works on dorsal vein to claim cashless treatment in a hospital which is on panel of medical insurance company. For acquisition of vein image, a NIR camera VF620 of 850 nm wavelength is used. The proposed model is applied on 1000 samples of dorsal vein patterns of 250 persons. The overall performance of the system was observed to be 97.95% with EER (Equal Error Rate)0.0435%.
Keywords: Veins Pattern Recognition, Biometric
Scope of the Article: Marketing and Social Sciences