Dorsal hand vein recognition system based on optimized texture features

被引：0
|
作者：
Liu F. [1 ,2 ]
Zong Y.-X. [1 ,2 ]
Kang B. [2 ]
Zhang Y.-M. [3 ]
Lin C.-X. [4 ]
Zhao H.-W. [5 ]
机构：
[1] National Key Laboratory for Automotive Simulation and Control, Jilin University, Changchun
[2] College of Communication Engineering, Jilin University, Changchun
[3] Electronic and Electrical Engineering Department, The University of Sheffield, Sheffield
[4] College of Information Science and Technology, Hainan University, Haikou
[5] College of Computer Science and Technology, Jilin University, Changchun
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2018年 / 48卷 / 06期
关键词：
Computer application; Dorsal hand vein recognition system; Texture feature optimization; Vein acquisition device;
D O I：
10.13229/j.cnki.jdxbgxb20170728
中图分类号：
学科分类号：
摘要：
In order to extract and match the texture features of dorsal hand vein, this paper presents a dorsal hand vein recognition system based on optimized texture features. First, we design a image acquisition device to collect vein images. Then, after image preprocessing and three-layer haar wavelet decomposition, we use different scales and directions of gabor kernel function to extract texture features of low-frequency sub-band images. Finally, PCA is used to reduce the dimensionality of features and the nearest neighbor classifier based on Euclidean distance is used to match the features. In this paper, a dorsal hand vein database of Jilin University is established. The experimental results show that the proposed recognition system can effectively improve the identification speed of features and the recognition rate can reach 98.5%. Good efforts on recognition accuracy and efficiency are achieved by the system. © 2018, Editorial Board of Jilin University. All right reserved.
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页码：1844 / 1850
页数：6
相关论文
共 15 条
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