Title: Dorsal hand-vein images recognition system based on grey level co-occurrence matrix and Tamura features

Authors: Abbas H. Hassin Alasadi; Moqdad Hanon Dawood

Addresses: Computer Science and Information Technology College, Basra University, Iraq ' Computer Science and Information Technology College, Basra University, Iraq

Abstract: Biometrics is the important area of distinguishing people using their behavioural characteristics. Until now, researcher and exporter increasing interest with vein pattern biometrics. A vein pattern is a massive link of blood vessels under a person's skin. Similar to fingerprints, in scientific sense, the shape of vascular patterns in the same part of the body has proved distinct from each other. The objective of this paper is to analyse vein images and to design and implement dorsal hand-vein recognition system that has the ability to segment vein and recognise each person based on his vein requires the presence of the human operator. The experimental results indicate that the MDC classifier achieves accuracy of 92% in the case of wavelet transform, and GLCM and Tamura features.

Keywords: biometric; vein images; feature extraction; DWT; grey level co-occurrence matrix; GLCM; Tamura.

DOI: 10.1504/IJAPR.2017.086586

International Journal of Applied Pattern Recognition, 2017 Vol.4 No.3, pp.207 - 225

Received: 20 Dec 2016
Accepted: 14 Mar 2017
Published online: 12 Sep 2017 *

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