Fast and accurate approaches for image and moving object segmentation

This paper introduces new two approaches for object extraction. The first one extracts the object in the image by separating the objects from the background. The second one extracts moving object in video sequences from the background. The approaches are based on background subtraction and edge information in the image. An initial spatial segmentation of the image is obtained by rainfalling watershed scheme. The resulting mask is used with a post-processing operation to remove the small regions and filling the holes of object region. After estimating the boundary of the object, the background subtraction process will be applied to get the final object. The proposed algorithm provides accurate results with different kinds of image. Simulation results demonstrated the efficiency of this method. In order to achieve object-based functionalities in image sequences, a new segmentation algorithm is applied to extract the video object planes (VOPs). The video approach is based on incorporating the spatial segmentation represented by fuzzy edge segmentation algorithm and temporal information represented by change detection. The simulation results demonstrated that the proposed algorithm can successfully extract moving objects from various sequences with different kinds of motion object. Nevertheless, the boundaries of the extracted object are not accurate enough to place them in different scenes.