应用科学学报 ›› 2014, Vol. 32 ›› Issue (1): 93-98.doi: 10.3969/j.issn.0255-8297.2014.01.015

• 信号与信息处理 • 上一篇    下一篇

稀疏超完备车辆识别与统计

逯鹏1, 娄亚飞1, 刘奉哲2, 李玉松1, 黄石磊1, 汤玉合1   

  1. 1. 郑州大学电气工程学院,郑州450001
    2. 中电投河南公司技术信息中心,郑州450016
  • 收稿日期:2013-06-03 修回日期:2013-07-16 出版日期:2014-01-31 发布日期:2013-07-16
  • 作者简介:逯鹏,博士,副教授,研究方向:智能感知、图像处理,E-mail: lupeng@zzu.edu.cn
  • 基金资助:

    国家自然科学基金(No.60841004,No.60971110,No.61172152);河南省青年骨干教师资助计划基金(No.2012GGJS-005);郑州
    市科技攻关基金(No.112PPTGY219-8)

Vehicle Identification and Counting Based on Sparse Over-Completeness

LU Peng1, LOU Ya-fei1, LIU Feng-zhe2, LI Yu-song1, HUANG Shi-lei1, TANG Yu-he1   

  1. 1. School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
    2. China Power Investment Henan Technical Information Center, Zhengzhou 450016, China
  • Received:2013-06-03 Revised:2013-07-16 Online:2014-01-31 Published:2013-07-16

摘要: 针对自动准确稳健的高速车辆统计问题,模拟视觉机制建立稀疏超完备表示模型,以图像单元作为处理对象,用少量非零响应稀疏系数表达目标图像的内在结构和本质属性,解决不同环境下、不同类别车辆的识别问题. 采用虚拟检测线技术设置动态车道进行在线统计,对多环境状况下车辆统计准确率达98.89%. 结果表明算法能有效抑制外界环境干扰,如光线变化和摄像机抖动等,其鲁棒性和准确率高于传统算法.

关键词: 稀疏超完备, 图像单元, 虚拟检测线, 车辆识别, 车辆统计

Abstract: To detect and count high-speed vehicles accurately and robustly, a sparse over-complete model is established to simulate the visual mechanism. The model uses image units as processing objects. It expresses the internal structure and essential attributes of the target image with a small amount of non-zero response sparse coefficients, and identifies different types of vehicles in different environments. Online counting of vehicles is achieved by setting dynamic lanes based on virtual detection lines. Accuracy of the vehicle counting reaches 98.89% under a variety of environmental conditions. The results show that the proposed algorithm can effectively suppress interference caused by external factors such as wind, light changes and camera shakes. It
has higher robustness and accuracy than traditional algorithms.  

Key words: sparse over-completeness, image unit, virtual detection line, vehicle identification, vehicle counting

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