A novel color clustering algorithm based on tensor voting is proposed. Each color feature vector is encoded by a second order tensor. Tensor voting is then applied to estimate the number of dominant colors and perform color clustering by exploiting the shape and data density of the color clusters. The experimental results show that the proposed method generates good results in image segmentation, especially in the case of images with multi-color texts.
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