Intelligent moving objects detection via adaptive frame differencing method

Authors:
Chun-Ming Tsai;Zong-Mu Yeh
Affiliations:
Department of Computer Science, Taipei Municipal University of Education, Taipei, Taiwan;Department of Mechatronic Technology, National Taiwan Normal University, Taipei, Taiwan
Venue:
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Year:
2013

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Abstract

The detection of moving objects is a critical first step in video surveillance, but conventional moving objects detection methods are not efficient or effective for certain types of moving objects: slow and fast. This paper presents an intelligent method to detect slow- and fast-moving objects simultaneously. It includes adaptive frame differencing, automatic thresholding, and moving objects localization. The adaptive frame differencing uses different inter-frames for frame differencing, the number depending on variations in the differencing image. The thresholding method uses a modified triangular algorithm to determine the threshold value and reduces most small noises. The moving objects localization uses six cascaded rules and bounding-boxes-based morphological operations to merge broken objects and remove noise objects. The fps value (maximum 72) depends on the speed of the objects. The number of inter-frames is inversely proportional to the speed. The results demonstrate that our method is more efficient than traditional frame differencing and background subtraction methods.