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Open Access

Big Data Oriented Novel Background Subtraction Algorithm for Urban Surveillance Systems

School of Computing and Communications, Lancaster University, InfoLab21, Lancaster, LA1 4WA.
Chinese Academy of Sciences Smart City Software Co. Ltd., China and also with Institute of Software Application Technology, Guangzhou & Chinese Academy of Sciences, Guangzhou 511458, China.
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Due to the tremendous volume of data generated by urban surveillance systems, big data oriented low-complexity automatic background subtraction techniques are in great demand. In this paper, we propose a novel automatic background subtraction algorithm for urban surveillance systems in which the computer can automatically renew an image as the new background image when no object is detected. This method is both simple and robust with respect to changes in light conditions.


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Big Data Mining and Analytics
Pages 137-145
Cite this article:
Hu L, Ni Q, Yuan F. Big Data Oriented Novel Background Subtraction Algorithm for Urban Surveillance Systems. Big Data Mining and Analytics, 2018, 1(2): 137-145.








Web of Science






Received: 30 December 2017
Accepted: 03 January 2018
Published: 12 April 2018
© The author(s) 2018