Adaptive Motion Segmentation for Changing Background
Yepeng Guan
DOI: 10.4236/jsea.2009.22014   PDF    HTML     5,100 Downloads   8,905 Views   Citations


Segmentation of moving objects efficiently from video sequence is very important for many applications. Background subtraction is a common method typically used to segment moving objects in image sequences taken from a statistic camera. Some existing algorithms cannot adapt to changing circumstances and require manual calibration in terms of specification of parameters or some hypotheses for changing background. An adaptive motion segmentation method is developed according to motion variation and chromatic characteristics, which prevents undesired corruption of the background model and does not consider the adaptation coefficient. RGB color space is selected instead of introducing complex color models to segment moving objects and suppress shadows. A color ratio for 4-connected neighbors of a pixel and multi-scale wavelet transformation are combined to suppress shadows. The mentioned approach is scene-independent and high correct segmentation. It has been shown that the approach is robust and efficient to detect moving objects by experiments.

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Y. Guan, "Adaptive Motion Segmentation for Changing Background," Journal of Software Engineering and Applications, Vol. 2 No. 2, 2009, pp. 96-102. doi: 10.4236/jsea.2009.22014.

Conflicts of Interest

The authors declare no conflicts of interest.


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