Title :
A Novel Method on Moving-Objects Detection Based on Background Subtraction and Three Frames Differencing
Author :
Lian XiaoFeng ; Zhang Tao ; Liu Zaiwen
Author_Institution :
Beijing Technol. & Bus. Univ., Beijing, China
Abstract :
This paper proposes a new method for moving-objects detection based on fusion of background subtraction and an improved three frames differencing. In the method, the adaptive background model is build by Gaussian model for each pixel in the image sequences, and combined with temporal differencing method to update the selective background, and simultaneously use background subtraction method to extract movement areas from the background model. Next, adopt the median filter and mathematical morphology operation to eliminate noise and the small areas of non-human motion parts. Finally obtain the complete reliable moving-objects. The experimental results show that the proposed method has high accuracy, and can meet the needs of real-time. So it can be applied in visual surveillance system effectively.
Keywords :
image fusion; image sequences; median filters; object detection; video surveillance; Gaussian model; adaptive background model; background subtraction; image sequences; mathematical morphology operation; median filter; moving-objects detection; three frames differencing; visual surveillance system; Cameras; Image segmentation; Image sequences; Layout; Morphology; Optical filters; Optical sensors; Paper technology; Pixel; Surveillance; Background subtraction; Background updating; Moving-object detection; Three frames differencing;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.132