A fully automated object extraction from video stream: a useful tool for distributed object-based browsing and content-based searching systems

This paper proposes an approach to automatically extract an accurate object from a video stream. The new approach consists of a skip-labeling algorithm for feature-based segmentation, an occlusion-killer algorithm for estimating accurately optical flow, and a shrink-merge tracking algorithm for tracking an object. The shrink-merge tracking algorithm is executed, based on the time continuity of moving-objects, using morphological image processing, such as dilation and erosion. The dilation and erosion are repeatedly executed using projection processing in which the object area in a following frame is derived from the object area in a current frame. The shrink-merge tracking algorithm can also project the area of a rotating object in a current frame on the rotating-object containing the newly appearing regions in the next frame. The automated object extraction method works satisfactory for objects which are moving nonlinearly within the video stream, and works satisfactory in 450 frames