An unsupervised natural image segmentation algorithm using mean histogram features

A new integrated feature distributions based natural image segmentation algorithm has been proposed. The proposed scheme uses histogram based new color texture extraction method which inherently combines color texture features rather then explicitly extracting it. Use of non parametric Bayesean clustering makes the segmentation framework fully unsupervised where no a priori knowledge about the number color textures regions are required. The feasibility and effectiveness of the proposed method have been demonstrated by various experiments using images of natural scenes. The experimental results reveal that superior segmentation results can be obtained through the proposed unsupervised segmentation framework.