NDLI: Study of the moving object detection used ICM and ARBS algorithm in enhanced fish-eye image

Content Provider	IEEE Xplore Digital Library
Author	Wu Jianhui Zhang Guoyun Guo Longyuan Yuan Shuai Chen Song
Copyright Year	2010
Description	Author affiliation: College of Information and communication engineering, Hunan Institute of Science & Technology, Yueyang, 414006, China (Wu Jianhui; Zhang Guoyun; Guo Longyuan; Yuan Shuai; Chen Song)
Abstract	The enhanced fish-eye lens can imaging an elliptical image which has higher resolution and information capability than normal fish-eye image. It can be used in the surveillance system to get the wide range monitoring. The moving object detection algorithm of the intersecting cortical model (ICM) and the Auto-adapted Renewal Background Subtraction (ARBS) are discussed, and have been used in the enhanced fish-eye surveillance system to detect the moving object. The experiment indicated that the ICM algorithm could detected the running track of the object and the ARBS algorithm could detected the many objects all-weather in enhance elliptical fish-eye images. Using the enhanced fish-eye lens and the ICM or ARBS algorithm to design the surveillance system, it not only has super wide field of view but also has better ability of moving object detection. It can be used in the field of traffic monitor and other security domain.
Starting Page	4053
Ending Page	4055
File Size	646423
Page Count	3
File Format	PDF
ISBN	9781424476169
e-ISBN	9781424476183
DOI	10.1109/ICISE.2010.5688618
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Charge coupled devices ICM Surveillance Imaging Object detection Enhanced fish-eye lens Motion detection ARBS Lenses
Content Type	Text
Resource Type	Article

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