首页    期刊浏览 2024年12月05日 星期四
登录注册

文章基本信息

  • 标题:Fuzzy Running Average and Fuzzy Background Subtraction: Concepts and Application
  • 本地全文:下载
  • 作者:Mohamad Hoseyn Sigari ; Naser Mozayani ; Hamid Reza Pourreza
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2008
  • 卷号:8
  • 期号:2
  • 页码:138-143
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Running average method and its modified version are two simple and fast methods for background modeling. In this paper, some weaknesses of running average method and standard background subtraction are mentioned. Then, a fuzzy approach for background modeling and background subtraction is proposed. For fuzzy background modeling, fuzzy running average is suggested. Background modeling and background subtraction algorithms are very commonly used in vehicle detection systems. To demonstrate the advantages of fuzzy running average and fuzzy background subtraction, these methods and their standard versions are compared in vehicle detection application. Experimental results show that fuzzy approach is relatively more accurate than classical approach.
  • 关键词:Fuzzy Background Modeling, Fuzzy Background Subtraction, Fuzzy Running Average, Vehicle Detection
国家哲学社会科学文献中心版权所有