A Novel Video Object Spatial Segmenting Strategy Based on Morphological Filtering

Video object extraction has been a hot topic in the field of modern information processing. This paper proposes a novel video object watershed segmenting strategy, which combines the merits of alternative sequential filtering by reconstruction and adaptive threshold algorithm. This strategy can automatically determine the structural element size of the morphological filter and the threshold value of nonlinear transformation as well. The iteration of opening-closing by reconstruction with gradually expanding structural elements guarantees the reduction of the segmented regions. Besides, the iteration makes it easier to distinguish the gradient of edge pixels and that of the pixels inside the plateaus, which facilitates removing the small regions of local gradient extrema by adaptive threshold algorithm. Experiment results show that the proposed strategy brings about satisfactory spatial segmenting results.