Finger-knuckle-print for identity verification based on difference images

Jooyoung Kim; Kangrok Oh; Andrew Beng Jin Teoh; Kar Ann Toh

doi:10.1109/ICIEA.2016.7603741

Finger-knuckle-print for identity verification based on difference images

Jooyoung Kim, Kangrok Oh, Andrew Beng Jin Teoh, Kar Ann Toh

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

In this paper, we propose to extract global directional features of finger-knuckle-print based on difference image for identity verification. In order to simplify the formulation for computational complexity reduction, the proposed horizontal and vertical difference images are generated based on matrix projection operation. Subsequently, a Heaviside step function is adopted for image ternarization. Next, we extract Fourier features from these ternary images by means of two-dimensional discrete Fourier transform. Finally, matching between extracted features is performed based on an Euclidean distance comparison. Our experiments on IIT Delhi Finger-Knuckle-Image Version 1.0 database show encouraging results in terms of verification accuracy and computing efficiency.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1073-1077
Number of pages	5
ISBN (Electronic)	9781509026050
DOIs	https://doi.org/10.1109/ICIEA.2016.7603741
Publication status	Published - 2016 Oct 19
Event	11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016 - Hefei, China Duration: 2016 Jun 5 → 2016 Jun 7

Publication series

Name	Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016

Other

Other	11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016
Country/Territory	China
City	Hefei
Period	16/6/5 → 16/6/7

Bibliographical note

Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant number: NRF-2015R1D1A1A09061316)

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Industrial and Manufacturing Engineering
Control and Optimization

Access to Document

10.1109/ICIEA.2016.7603741

Cite this

Kim, J., Oh, K., Teoh, A. B. J., & Toh, K. A. (2016). Finger-knuckle-print for identity verification based on difference images. In Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016 (pp. 1073-1077). [7603741] (Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA.2016.7603741

Kim, Jooyoung ; Oh, Kangrok ; Teoh, Andrew Beng Jin et al. / Finger-knuckle-print for identity verification based on difference images. Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1073-1077 (Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016).

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abstract = "In this paper, we propose to extract global directional features of finger-knuckle-print based on difference image for identity verification. In order to simplify the formulation for computational complexity reduction, the proposed horizontal and vertical difference images are generated based on matrix projection operation. Subsequently, a Heaviside step function is adopted for image ternarization. Next, we extract Fourier features from these ternary images by means of two-dimensional discrete Fourier transform. Finally, matching between extracted features is performed based on an Euclidean distance comparison. Our experiments on IIT Delhi Finger-Knuckle-Image Version 1.0 database show encouraging results in terms of verification accuracy and computing efficiency.",

author = "Jooyoung Kim and Kangrok Oh and Teoh, {Andrew Beng Jin} and Toh, {Kar Ann}",

note = "Funding Information: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant number: NRF-2015R1D1A1A09061316) Publisher Copyright: {\textcopyright} 2016 IEEE.; 11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016 ; Conference date: 05-06-2016 Through 07-06-2016",

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doi = "10.1109/ICIEA.2016.7603741",

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Kim, J, Oh, K, Teoh, ABJ & Toh, KA 2016, Finger-knuckle-print for identity verification based on difference images. in Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016., 7603741, Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1073-1077, 11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016, Hefei, China, 16/6/5. https://doi.org/10.1109/ICIEA.2016.7603741

Finger-knuckle-print for identity verification based on difference images. / Kim, Jooyoung; Oh, Kangrok; Teoh, Andrew Beng Jin et al.

Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1073-1077 7603741 (Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant number: NRF-2015R1D1A1A09061316) Publisher Copyright: © 2016 IEEE.

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N2 - In this paper, we propose to extract global directional features of finger-knuckle-print based on difference image for identity verification. In order to simplify the formulation for computational complexity reduction, the proposed horizontal and vertical difference images are generated based on matrix projection operation. Subsequently, a Heaviside step function is adopted for image ternarization. Next, we extract Fourier features from these ternary images by means of two-dimensional discrete Fourier transform. Finally, matching between extracted features is performed based on an Euclidean distance comparison. Our experiments on IIT Delhi Finger-Knuckle-Image Version 1.0 database show encouraging results in terms of verification accuracy and computing efficiency.

AB - In this paper, we propose to extract global directional features of finger-knuckle-print based on difference image for identity verification. In order to simplify the formulation for computational complexity reduction, the proposed horizontal and vertical difference images are generated based on matrix projection operation. Subsequently, a Heaviside step function is adopted for image ternarization. Next, we extract Fourier features from these ternary images by means of two-dimensional discrete Fourier transform. Finally, matching between extracted features is performed based on an Euclidean distance comparison. Our experiments on IIT Delhi Finger-Knuckle-Image Version 1.0 database show encouraging results in terms of verification accuracy and computing efficiency.

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Kim J, Oh K, Teoh ABJ , Toh KA. Finger-knuckle-print for identity verification based on difference images. In Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1073-1077. 7603741. (Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016). doi: 10.1109/ICIEA.2016.7603741

Finger-knuckle-print for identity verification based on difference images

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