Paper
19 March 2013 An improved background segmentation method for ghost removals
Author Affiliations +
Proceedings Volume 8663, Video Surveillance and Transportation Imaging Applications; 86630W (2013) https://doi.org/10.1117/12.2008653
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
Video surveillance has become common for the maintenance of security in a wide variety of applications. However, the increasingly large amounts of data produced from multiple video camera feeds is making it increasingly difficult for human operators to monitor the imagery for activities likely to give rise to threats. This has led to the development of different automated surveillance systems that can detect, track and analyze video sequences both online and offline and report potential security risks. Segmentation of objects is an important part of such systems and numerous background segmentation techniques have been used in the literature. One common challenge faced by these techniques is adaption in different lighting environments. A new improved background segmentation technique has been presented in this where the main focus is to accurately segment potentially important objects by reducing the overall false detection rate. Historic edge maps and tracking results are analyzed for this purpose. The idea is to obtain an up to date edge map of the segmented region highlighted as foreground areas and compare them with the stored results. The edge maps are obtained using a novel adaptive edge orientation based technique where orientation of the edge is used. Experimental results have shown that the discussed technique gives over 85% matching results even in severe lighting changes.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Waqas Hassan, Philip Birch, Rupert Young, and Chris Chatwin "An improved background segmentation method for ghost removals", Proc. SPIE 8663, Video Surveillance and Transportation Imaging Applications, 86630W (19 March 2013); https://doi.org/10.1117/12.2008653
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Light sources and illumination

Video surveillance

Manganese

Video

Cameras

Computer security

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