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In this paper, we present an unsupervised color image segmentation method using voting-based feature analysis and adaptive mean shift. This algorithm is based on the tensor voting approach - a unified computational framework for the inference of multiple salient structures. An unsupervised segmentation algorithm using the adaptive mean shift clustering method is applied to the reduced feature space...
Existing methods for color image segmentation using diffusion can't preserve contour information and noises with high gradients become more salient as the number of times of the diffusion increases, resulting in over-segmentation when applied to watershed. This paper proposes a new method for color image segmentation by applying morphological operations together with nonlinear diffusion. Morphological...
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