Palmprint texture analysis using derivative of Gaussian filters

Xiangqian Wu; Kuanquan Wang; David Zhang

doi:10.1109/ICCIAS.2006.294235

Palmprint texture analysis using derivative of Gaussian filters

Xiangqian Wu^*
, Kuanquan Wang
, David Zhang

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology
Hong Kong Polytechnic University

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

49 Scopus citations

Abstract

This paper presents a novel approach of palmprint texture analysis based on the derivative of gaussian filter. In this approach, the palmprint image is respectively preprocessed along horizontal and vertical direction using derivative of gaussian (DoG) Filters. And then the palmprint is encoded according to the sign of the value of each pixel of the filtered images. This code is called DoGCode of the palmprint. The size of DoGCode is 256 bytes. The similarity of two DoGCode is measured using their Hamming distance. This approach is tested on the PolyU Palmprint Database, which containing 7605 samples from 392 palms, and the EER is 0.19%, which is comparable with the existing palmprint recognition methods.

Original language	English
Title of host publication	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Publisher	IEEE Computer Society
Pages	751-754
Number of pages	4
ISBN (Print)	1424406056, 9781424406050
DOIs	https://doi.org/10.1109/ICCIAS.2006.294235
State	Published - 2006
Externally published	Yes
Event	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 - Guangzhou, China Duration: 3 Oct 2006 → 6 Oct 2006

Publication series

Name	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Volume	1

Conference

Conference	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Country/Territory	China
City	Guangzhou
Period	3/10/06 → 6/10/06

Access to Document

10.1109/ICCIAS.2006.294235

Cite this

Wu, X., Wang, K., & Zhang, D. (2006). Palmprint texture analysis using derivative of Gaussian filters. In 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 (pp. 751-754). Article 4072188 (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 1). IEEE Computer Society. https://doi.org/10.1109/ICCIAS.2006.294235

@inproceedings{a73d0612ea5b4d0da17baad6947aa533,

title = "Palmprint texture analysis using derivative of Gaussian filters",

abstract = "This paper presents a novel approach of palmprint texture analysis based on the derivative of gaussian filter. In this approach, the palmprint image is respectively preprocessed along horizontal and vertical direction using derivative of gaussian (DoG) Filters. And then the palmprint is encoded according to the sign of the value of each pixel of the filtered images. This code is called DoGCode of the palmprint. The size of DoGCode is 256 bytes. The similarity of two DoGCode is measured using their Hamming distance. This approach is tested on the PolyU Palmprint Database, which containing 7605 samples from 392 palms, and the EER is 0.19\%, which is comparable with the existing palmprint recognition methods.",

author = "Xiangqian Wu and Kuanquan Wang and David Zhang",

year = "2006",

doi = "10.1109/ICCIAS.2006.294235",

language = "英语",

isbn = "1424406056",

series = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006",

publisher = "IEEE Computer Society",

pages = "751--754",

booktitle = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006",

address = "美国",

note = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 ; Conference date: 03-10-2006 Through 06-10-2006",

}

Wu, X , Wang, K & Zhang, D 2006, Palmprint texture analysis using derivative of Gaussian filters. in 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006., 4072188, 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006, vol. 1, IEEE Computer Society, pp. 751-754, 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006, Guangzhou, China, 3/10/06. https://doi.org/10.1109/ICCIAS.2006.294235

Palmprint texture analysis using derivative of Gaussian filters. / Wu, Xiangqian ; Wang, Kuanquan; Zhang, David.
2006 International Conference on Computational Intelligence and Security, ICCIAS 2006. IEEE Computer Society, 2006. p. 751-754 4072188 (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 1).

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

TY - GEN

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AU - Wu, Xiangqian

AU - Wang, Kuanquan

AU - Zhang, David

PY - 2006

Y1 - 2006

N2 - This paper presents a novel approach of palmprint texture analysis based on the derivative of gaussian filter. In this approach, the palmprint image is respectively preprocessed along horizontal and vertical direction using derivative of gaussian (DoG) Filters. And then the palmprint is encoded according to the sign of the value of each pixel of the filtered images. This code is called DoGCode of the palmprint. The size of DoGCode is 256 bytes. The similarity of two DoGCode is measured using their Hamming distance. This approach is tested on the PolyU Palmprint Database, which containing 7605 samples from 392 palms, and the EER is 0.19%, which is comparable with the existing palmprint recognition methods.

AB - This paper presents a novel approach of palmprint texture analysis based on the derivative of gaussian filter. In this approach, the palmprint image is respectively preprocessed along horizontal and vertical direction using derivative of gaussian (DoG) Filters. And then the palmprint is encoded according to the sign of the value of each pixel of the filtered images. This code is called DoGCode of the palmprint. The size of DoGCode is 256 bytes. The similarity of two DoGCode is measured using their Hamming distance. This approach is tested on the PolyU Palmprint Database, which containing 7605 samples from 392 palms, and the EER is 0.19%, which is comparable with the existing palmprint recognition methods.

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DO - 10.1109/ICCIAS.2006.294235

M3 - 会议稿件

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SN - 1424406056

SN - 9781424406050

T3 - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

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BT - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

PB - IEEE Computer Society

T2 - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

Y2 - 3 October 2006 through 6 October 2006

ER -

Palmprint texture analysis using derivative of Gaussian filters

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