Finger vein recognition system for authentication of patient data in hospital

Janney, J Bethanney; Divakaran, Sindu; Shankar, G.Uma

doi:10.22376/ijpbs.2017.8.2.b5-10

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Using Gaussian Weighted Spatial Curve Filtering (GWSCF), they extracted the features from the finger vein images. The same year, Janney et al [ 88 ] in their method used Discrete Wavelet Transform (DWT). Discrete Wavelet Transform decomposes the image into two bands: low-pass components and high-pass components.…”

Section: Finger Vein Feature Extractionmentioning

confidence: 99%

Feature Extraction for Finger-Vein-Based Identity Recognition

et al. 2021

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This paper aims to provide a brief review of the feature extraction methods applied for finger vein recognition. The presented study is designed in a systematic way in order to bring light to the scientific interest for biometric systems based on finger vein biometric features. The analysis spans over a period of 13 years (from 2008 to 2020). The examined feature extraction algorithms are clustered into five categories and are presented in a qualitative manner by focusing mainly on the techniques applied to represent the features of the finger veins that uniquely prove a human’s identity. In addition, the case of non-handcrafted features learned in a deep learning framework is also examined. The conducted literature analysis revealed the increased interest in finger vein biometric systems as well as the high diversity of different feature extraction methods proposed over the past several years. However, last year this interest shifted to the application of Convolutional Neural Networks following the general trend of applying deep learning models in a range of disciplines. Finally, yet importantly, this work highlights the limitations of the existing feature extraction methods and describes the research actions needed to face the identified challenges.

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Section: Finger Vein Feature Extractionmentioning

confidence: 99%

Feature Extraction for Finger-Vein-Based Identity Recognition

et al. 2021

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“…When a new medical insurance is issued to a customer, the details of customer along with the vein patterns (in encrypted form) is accessed by the hospital from insurance company server. Some such systems are already in use, but in different way like, Bethanny et al [23] used finger vein data of all patients to keep their record for further biometric identification. Policy Holder -There are two ways in which a policy holder can be treated: (i) Planned cashless treatment (as some disease is diagnosed) and (ii) Causality (as insurance policy holder meets with some causality).…”

Section: The Proposed Modelmentioning

confidence: 99%

SIFT based Dorsal Vein Recognition System for Cashless Treatment through Medical Insurance

2019

IJITEE

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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%

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Finger vein recognition system for authentication of patient data in hospital

Cited by 2 publications

References 13 publications

Feature Extraction for Finger-Vein-Based Identity Recognition

Feature Extraction for Finger-Vein-Based Identity Recognition

SIFT based Dorsal Vein Recognition System for Cashless Treatment through Medical Insurance

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