Title: Intelligent technique for human authentication using hand vein

Authors: Mona A. Ahmed; Mohamed Roushdy; Abdel-Badeeh M. Salem

Addresses: Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Abbassia, 11566, Cairo, Egypt ' Computer Science Department, Dean of Faculty of Computers and Information Technology, Future University in Egypt, New Cairo, 11835, Egypt ' Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Abbassia, 11566, Cairo, Egypt

Abstract: In this paper, we propose a new intelligent technique to authenticate human using dorsal hand vein (DHV) pattern. Recently, authentication was adopted by smart hospitals in many countries as an intelligent tool for patient identification to prevent insurance and can connect the patient with his or her medical record securely. In this paper we developed an image analysis technique to extract region of interest (ROI) from DHV image. After extracting ROI we design a sequence of preprocessing steps to improve hand vein images using Median filter, Wiener filter and contrast limited adaptive histogram equalisation (CLAHE) to enhance hand vein image. Our smart technique is based on the following intelligent algorithms, namely; principal component analysis (PCA) algorithm for feature extraction and k-nearest neighbours (K-NN) classifier for matching operation. This technique has been applied on the Bosphorus Hand Vein Database. The experimental results show that the result of (CRR) is 91.2%.

Keywords: biometric; DHV; dorsal hand vein; computational intelligence; feature extraction; PCA; principal component analysis; K-NN; k-nearest neighbours; machine learning.

DOI: 10.1504/IJDS.2020.115853

International Journal of Data Science, 2020 Vol.5 No.4, pp.263 - 275

Received: 15 May 2020
Accepted: 06 Jul 2020
Published online: 25 Jun 2021 *

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