Palm Vein Verification Using Multiple Features and Locality Preserving Projections

Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many...

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Main Authors: Ali Mohsin Al-juboori, Wei Bu, Xiangqian Wu, Qiushi Zhao
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/246083
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author Ali Mohsin Al-juboori
Wei Bu
Xiangqian Wu
Qiushi Zhao
author_facet Ali Mohsin Al-juboori
Wei Bu
Xiangqian Wu
Qiushi Zhao
author_sort Ali Mohsin Al-juboori
collection DOAJ
description Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person’s skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%.
format Article
id doaj-art-19f434c4b6ca4b3e8e2af470b3389ec3
institution Kabale University
issn 2356-6140
1537-744X
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-19f434c4b6ca4b3e8e2af470b3389ec32025-08-20T03:54:21ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/246083246083Palm Vein Verification Using Multiple Features and Locality Preserving ProjectionsAli Mohsin Al-juboori0Wei Bu1Xiangqian Wu2Qiushi Zhao3School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaDepartment of New Media Technology and Arts, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaBiometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person’s skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%.http://dx.doi.org/10.1155/2014/246083
spellingShingle Ali Mohsin Al-juboori
Wei Bu
Xiangqian Wu
Qiushi Zhao
Palm Vein Verification Using Multiple Features and Locality Preserving Projections
The Scientific World Journal
title Palm Vein Verification Using Multiple Features and Locality Preserving Projections
title_full Palm Vein Verification Using Multiple Features and Locality Preserving Projections
title_fullStr Palm Vein Verification Using Multiple Features and Locality Preserving Projections
title_full_unstemmed Palm Vein Verification Using Multiple Features and Locality Preserving Projections
title_short Palm Vein Verification Using Multiple Features and Locality Preserving Projections
title_sort palm vein verification using multiple features and locality preserving projections
url http://dx.doi.org/10.1155/2014/246083
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AT weibu palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections
AT xiangqianwu palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections
AT qiushizhao palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections