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Authors: Aditya Nigam 1 and Phalguni Gupta 2

Affiliations: 1 Indian Institute of Technology Mandi (IIT Mandi), India ; 2 National Institute of Technical Teacher’s & Research (NITTTR), India

Keyword(s): Finger-Knuckle-Print, FKP, Curvature Gabor Filter, Segmentation, Authentication.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Multimedia Forensics

Abstract: Biometric based human recognition is a most obvious method for automatically resolving personal identity with high reliability. In this paper we present a novel finger-knuckle-print ROI extraction algorithm. The basic Gabor filter is modified to Curvature Gabor Filter (CGF) to obtain central knuckle line and central knuckle point which are further used to extract FKP ROI image. Largest public FKP database is used for testing which consists of 7;920 images collected from 660 different fingers. The results has been compared with the only other existing Convex Direction Coding (CDC) ROI extraction algorithm. It has been observed that the proposed algorithm achieves better performance with EER drop percentage more than 20% in all experiments. This suggests that the proposed CGF algorithm has been extracting ROI more consistently then CDC and hence can facilitates any finger-knuckle-print based biometric systems.

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Paper citation in several formats:
Nigam, A. and Gupta, P. (2016). Finger-Knuckle-Print ROI Extraction using Curvature Gabor Filter for Human Authentication. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 3: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 364-371. DOI: 10.5220/0005724103640371

@conference{visapp16,
author={Aditya Nigam. and Phalguni Gupta.},
title={Finger-Knuckle-Print ROI Extraction using Curvature Gabor Filter for Human Authentication},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 3: VISAPP},
year={2016},
pages={364-371},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005724103640371},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 3: VISAPP
TI - Finger-Knuckle-Print ROI Extraction using Curvature Gabor Filter for Human Authentication
SN - 978-989-758-175-5
IS - 2184-4321
AU - Nigam, A.
AU - Gupta, P.
PY - 2016
SP - 364
EP - 371
DO - 10.5220/0005724103640371
PB - SciTePress

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