A Slow-Moving-Object Segmentation Technology Based on  MRF Under Complex Background

A slow-moving-object segmentation technology based on MRF under complex background is proposed in this paper which adopts the technology of background suppression based on inverted optical flow field and the plan of gray field modeling based on weighted histogram. The technology of background suppression firstly conducts inverted optical flow transformation on adjacent frame to align object projections， then segments the object from the background by a given threshold value based on the adjacent frame difference to obtain coarse segmentation of the images; The plan of gray field modeling firstly distributes trust degree to pixels of the coarse segmentation image， then establishes weighted histogram adopting the statistics of trust degrees， and finally build exact gray field modeling based on the weighted histogram. Based on these， video images are segmented under the MAP-MRF framework. Experiments are dong and the results are evaluated by the criterias of spatial accuracy and temporal coherency which shows that these metods are valid and robust.