By Topic

Motion Object and Regional Detection Method Using Block-Based Background Difference Video Frames

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Jiwoong Bang ; Dept. of Comput. Sci., Dankook Univ., Yongin, South Korea ; Daewon Kim ; Hyeonsang Eom

Smart CCTV (Closed-Circuit Television) technology has increasingly been developed in the last few years to judge the situation and notify the administrator or take immediate action for security and surveillance reasons. Currently the methods to detect object motion typically include the Frame Difference Method (FDM) which can detect moving objects and the Background Subtraction Method (BSM) which is able to detect motionless objects. Those results can be obtained only if there were some background images ready in advance. The Adaptive Background Subtraction Method (ABSM) also could not recognize an object very well if there are rapid scene changes or an object does not move relatively for a long time. To resolve such a problem, in this research, a filmed image has been divided into the regular sized blocks and then, only the necessary parts of the previous frame image are updated in real-time and a background image was generated so that it is insensible to surrounding environment changes such as object motion, noise or light variations. We proposed a novel moving object detection method which showed high performance with regard to the MSE (Mean Squared Error) and the accuracy of detecting the moving object contours compared to other existing methods. We also evaluated quantitatively the detectability for a moving object region by quickly creating a background image even if it is difficult to shoot a background image or we do not have the baseline image prepared in advance. The proposed method could be used for cases that any background image does not exist or hard to be generated. It is also good for observation of many places at the same time with only a single CCTV system since it is especially robust to abrupt scene changes.

Published in:

Embedded and Real-Time Computing Systems and Applications (RTCSA), 2012 IEEE 18th International Conference on

Date of Conference:

19-22 Aug. 2012