[1]于爱华,王洪安.基于特征优化与稀疏表示的3D掌纹分类[J].浙江科技学院学报,2017,(06):450-456.[doi:10.3969/j.issn.1671-8798.2017.06.009]
 YU Aihua,WANG Hongan.3D palm-print sparse representation classification based on optimized features[J].,2017,(06):450-456.[doi:10.3969/j.issn.1671-8798.2017.06.009]
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基于特征优化与稀疏表示的3D掌纹分类(/HTML)
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《浙江科技学院学报》[ISSN:1001-3733/CN:61-1062/R]

卷:
期数:
2017年06期
页码:
450-456
栏目:
出版日期:
2017-12-14

文章信息/Info

Title:
3D palm-print sparse representation classification based on optimized features
文章编号:
1671-8798(2017)06-0450-07
作者:
于爱华王洪安
浙江科技学院 自动化与电气工程学院,杭州 310023
Author(s):
YU Aihua WANG Hongan
School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China
关键词:
3D掌纹识别 压缩感知 投影矩阵优化 稀疏表示
分类号:
TP 391.41; TN911.7
DOI:
10.3969/j.issn.1671-8798.2017.06.009
文献标志码:
A
摘要:
针对大数据背景下3D掌纹技术存在的问题,提出一种基于优化投影矩阵的3D掌纹稀疏表示识别技术架构。系统首先提取3D掌纹表面类型特征,然后利用分块方向梯度直方图构成训练样本,通过优化设计投影矩阵,使得同类掌纹投影特征互相关性变大,异类掌纹投影特征互相关性变小; 最后利用投影后3D掌纹特征稀疏表示分类,并比较L0/L1/L2范数各种快速算法性能。通过投影优化后的系统,在识别率和实时性上都有所改善,仿真实验证实了研究工作的有效性。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-05-09
基金项目: 浙江省教育厅科研计划项目(Y201430687)
通信作者: 于爱华(1975— ),男,江苏省海安人,工程师,博士研究生,主要从事数字信号处理研究。E-mail:yuaihua_seu@163.com。
更新日期/Last Update: 1900-01-01