Analysis of Vascular Pattern Recognition Using Neural Network

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Author(s)

Navjot Kaur 1 Amardeep Singh 1

1. Punjabi University, Patiala (147002), India

* Corresponding author.

DOI: https://doi.org/10.5815/ijmsc.2015.03.02

Received: 31 May 2015 / Revised: 4 Jul. 2015 / Accepted: 10 Aug. 2015 / Published: 8 Sep. 2015

Index Terms

Neural Network, Scale Invariant Feature Transform, False Acceptation Rate, False Rejection Rate, Canny Edge Detector

Abstract

Biometric identification using vein patterns is a recent technique. The vein patterns are unique to each individual even in twins and they don't change over age except their size. As veins are beneath the skin it is difficult to forge. BOSPHOROUS hand vein database is used in this work. Hand vein images are uploaded first and key points using Scale Invariant Feature Transform (SIFT) are extracted. Then the neural network is used for training these images. Finally neural network is used for testing these images to check whether the image used for testing matches with the existing database or not. Results are computed like False Acceptation Rate (FAR), False Rejection Rate (FRR), accuracy and error per bit stream.

Cite This Paper

Navjot Kaur, Amardeep Singh ,"Analysis of Vascular Pattern Recognition Using Neural Network", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.1, No.3, pp.9-19, 2015.DOI: 10.5815/ijmsc.2015.03.02

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