A Novel Fuzzy Background Subtraction Method Based on Cellular Automata for Urban Traffic Applications
Computational structure of cellular automata has attracted researchers and vastly been used in various fields of science.They are especially suitable for modeling natural systems that can be described as massive collections of simple objects interacting locally with each other,such as motion detection in image processing.On the other hand,extraction of moving objects from an image sequence is a fundamental problem in dynamic image analysis Nowadays background modeling and subtraction algorithms are commonly used in real-time urban traffic applications for detecting and tracking vehicles and monitoring streets.In this paper by the use of cellular automata,a novel fuzzy approach for background subtraction with a particular interest to the problem of vehicle detection is presented.Our experimental results demonstrate that fuzzy-cellular system is much more efficient,robust and accurate than classical approaches.Our experimental results demonstrate that the fuzzycellular system is much more efficient,robust and accurate than classical approaches.
Moein Shakeri Hossein Deldari Homa Foroughi Alireza Saberi Aabed Naseri
Department of Computer Engineering,Ferdowsi University of Mashhad,Iran Department of Electrical and Computer Engineering,Concordia University,Canada
国际会议
9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)
北京
英文
2008-10-26（万方平台首次上网日期，不代表论文的发表时间）