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Abstract

Finger vein recognition has emerged as the robust biometric modality because of their unique vein pattern that can be captured using near infrared spectrum. The large scale finger vein based biometric solutions demand the need of searching the probe finger vein sample against the large collection of gallery samples. In order to improve the reliability in searching for the suitable identity in the large-scale finger vein database, it is essential to introduce the finger vein indexing and retrieval scheme. In this work, we present a novel finger vein indexing and retrieval scheme based on unsupervised clustering. Recently, biometrics such as fingerprints, faces and irises recognition have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins to identify individuals at a high level of accuracy. This paper proposes new algorithms for finger vein recognition. This research presents the following three advantages and contributions compared to previous works. First, we extracted local information of the finger veins based on a LBP (Local Binary Pattern) without segmenting accurate finger vein regions. Second, the global information of the finger veins based on Wavelet transform was extracted. Third, two score values by the LBP and Wavelet transform were combined by the Minimum distance classifer. Currently, passwords, Personal Identification cards are used for personal identification. However, cards can be stolen, and passwords and numbers can be guessed or forgotten. To solve these problems, biometric authentication technology, which identifies people by their unique biological information, is attracting attention. Finger vein recognition is that it is not affected by dryness or roughness of skin or by physical injury on surface of the hand but sometimes the temperature and humidity can affect the quality of the captured image.

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How to Cite
V.Shanmugavalli, S.Radhi Priya, M.Priyanka, A.Ramya, & M.Thillaikarasi. (2019). A novel approach of finger vein recognition for personal authentication . International Journal of Intellectual Advancements and Research in Engineering Computations, 7(1), 301–307. Retrieved from https://ijiarec.com/ijiarec/article/view/980