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Texture Based Vein Biometrics for Human Identification: A Comparative Study

Version 2 2024-06-06, 03:41
Version 1 2022-11-24, 00:03
conference contribution
posted on 2024-06-06, 03:41 authored by K Bashar, Manzur MurshedManzur Murshed
Hand vein biometric is an important modality for human authentication and liveness detection in many applications. Reliable feature extraction is vital to any biometric system. Over the past years, two major categories of vein features, namely vein structures and vein image textures, were proposed for hand dorsal vein based biometric identification. Of them, texture features seem important as it can combine skin micro-textures along with vein properties. In this study, we have performed a comparative study to identify potential texture features and feature-classifier combination that produce efficient vein biometric systems. Seven texture features (HOG, GABOR, GLCM, SSF, DWT, WPT, and LBP) and three multiclass classifiers (LDA, ESVM, and KNN) were explored towards the supervised identification of human from vein images. An experiment with 400 infrared (IR) hand images from 40 adults indicates the superior performance of the histogram of oriented gradients (HOG) and simple local statistical feature (SSF) with LDA and ESVM classifiers in terms of average accuracy (> 90%), average Fscore (> 58%) and average specificity (>93%). The decision-level fusion of the LDA and ESVM classifier with single texture features showed improved performances (by 2.2 to 13.2% of average Fscore) over individual classifier for human identification with IR hand vein images.

History

Volume

2

Pagination

571-576

Location

Tokyo, Japan

Start date

2018-07-23

End date

2018-07-27

ISSN

0730-3157

ISBN-13

9781538626672

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

Hasan K

Title of proceedings

COMPSAC 2018 : Staying Smarter in a Smartening World : Proceedings of the Computer Software and Applications 2018 conference

Event

Computer Software and Applications. Conference (42nd : 2018 : Tokyo, Japan)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Series

Proceedings International Computer Software and Applications Conference

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