Unsupervised Natural Image Segmentation Using Mean Histogram Features

A new histogram feature 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. A non parametric Bayesean clustering is employed to make the segmentation framework fully unsupervised where no a priori knowledge about the number and types of regions are required. The performance of the proposed method have been demonstrated by various experiments using images of natural scenes. The experimental results indicates that superior segmentation results can be obtained through the proposed unsupervised natural image segmentation algorithm.