An accurate semi-automatic segmentation scheme based on watershed and change detection mask
C. De Roover, Moncef Gabbouj, Benoit M. M. Macq · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
This paper presents a region-based segmentation method extracting automatically moving objects from video sequences. Non-moving objects can also be segmented by using a graphical user interface. The segmentation scheme is inspired from existing methods based on the watershed algorithm. The over-segmented regions resulting from the watershed are first organized in a binary partition tree according to a similarity criterion. This tree aims to determine the fusion order. Every region is then fused with the most similar neighbour according to a spatio-temporal criterion regarding the region colors and the temporal colors continuity. The fusion can be stopped either by fixing a priori the final number of regions, or by markers given through the graphical user interface. Markers are also used to assign a class to non-moving objects. Classification of moving objects is automatically obtained by computing the Change Detection Mask. To get a better accuracy on the contours of the segmented objects, we perform a simple post-processing filter to refine the edges between different video object planes.