Image Segmentation based on Inter-feature Distance Maps

In this paper we present an unsupervised colour-texture segmentation method. The novelty of this new approach relies on the definition of the interfeature distance map, which combines different textural properties, either those due to chromaticity variations or those due to intensity changes. The proposed framework works on a multi-channel representation that directly depends on the basic colours perceived in an image, trying to avoid the spatial correlation of usual 3D representations of colour. The textural information derived from intensity changes is added to the multi-channel representation and finally, chromaticity and intensity are combined with the inter-feature distance maps. The behaviour of the approach is tested on a set of natural and synthetic images to demonstrate the capabilities to deal with some representative types of colour-textures which are suggested in this work.