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Region growing (RG) is one of the simplest, yet most effective, image segmentation approaches for segmenting lung regions within CT scans [23, 26].
Motion segmentation approaches like [53, 54] sparsely segment point trajectories based on the geometric coherency of the motion.
General mesh segmentation approaches are not directly suited for segmenting dental meshes because they lack adjustments to handle complex tooth shapes and teeth arrangements.
Besides the typical semantic segmentation approaches, many approaches aim at the accuracy improvement of object segment, such as the interactive segmentation [16 18] and the co-segmentation [19 21].
A review of traditional segmentation approaches is given in [24].
Many segmentation approaches for background subtraction have been proposed over the past decades [5 9].
Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls.
Early manual segmentation approaches used very basic tools such as a pencil, spline widget or paintbrush.
Segmentation approaches may be categorised according to the amount of user input involved.
The paper analyses main segmentation approaches for multimedia services from the viewpoint of their features.
In the most of the existing color image segmentation approaches, the definition of a region is based on similar color.
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