吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 822-827.doi: 10.13229/j.cnki.jdxbgxb201403039

• 论文 • 上一篇    下一篇

基于稀疏表示的多类融合样本中特定目标识别

查长军1,2,韦穗1,杨海蓉3,丁大为1   

  1. 1.安徽大学 计算智能与信号处理教育部重点实验室,合肥 230039;
    2.合肥学院 机器视觉与智能控制技术重点实验室,合肥 230601;
    3.合肥师范学院 数学系,合肥 230061
  • 收稿日期:2013-02-26 出版日期:2014-03-01 发布日期:2014-03-01
  • 通讯作者: 韦穗(1946),女,教授,博士生导师.研究方向:压缩感知,图像处理与三维全息显示.E-mail:swei@ahu.edu.cn E-mail:zcj_longman@sina.com
  • 作者简介:查长军(1980),男,博士研究生.研究方向:光学成像与信号处理.E-mail:zcj_longman@sina.com
  • 基金资助:
    NSFC-广东联合基金项目(U1201255);高等学校博士学科点专项科研基金项目(20113401130001);国家自然科学青年基金项目(61201227);安徽省自然科学基金青年项目(1208085QF114);安徽省高校省级自然科学一般项目(KJ2011B131,KJ2013B224).

Special object recognition based on sparse representation in multiclass fusion sample

ZHA Chang-jun1,2,WEI Sui1,YANG Hai-rong3,DING Da-wei1   

  1. 1.Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei 230039,China;
    2.Key Laboratory of Machine Vision and Intelligence Control Technology, Hefei University, Hefei 230601,China;
    3.Department of Mathematics, Hefei Normal University,Hefei 230061,China
  • Received:2013-02-26 Online:2014-03-01 Published:2014-03-01

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摘要： 针对WSN及轮廓检测系统的特点,给出了一种基于WSN的数据处理方法。该方法首先通过主分量分析提取样本特征,然后采用叠加方式对不同样本的特征进行融合,给出数学模型;并以此模型为基础,提出一种新的基于稀疏表示的多类融合样本中特定目标识别算法,该算法根据超完备字典下主要非零系数的分布情况识别出特定目标;数值仿真与实验结果验证了本文算法的有效性,综合性能优于传统方法。

关键词: 信息处理技术, 无线传感器网络, 稀疏表示, 轮廓识别, 无人值守地面传感器

Abstract: According to the characteristics of Wireless Sensor Network (WSN) and the profile detecting system, a data processing method based on WSN is proposed. In this method, first, the sample features are extracted by principal component analysis; then, the features of different samples were fused using accumulate mode. A mathematical model was given and on the basis of this model, a novel algorithm of special object recognition based on sparse representation in multiclass fusion sample was proposed. This algorithm recognizes the special target according to distribution of the main non-zero coefficients under an over-complete dictionary. Numerical simulation and experimental results demonstrate the effectiveness of the proposed algorithm, the comprehensive performance is better than the traditional methods.

Key words: information processing, wireless sensor network, sparse representation, profiling recognition, unattended ground sensor

中图分类号: 

  • TN911.74
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