An approach for perceptual segmentation of colour image textures is described. A multiscale representation of the texture image, generated by a multiband smoothing algorithm based on human psychophysical measurements of colour appearance is used as the input. Initial segmentation is achieved by applying a clustering algorithm to the image at the coarsest level of smoothing. Using these isolated \em core clusters 3D colour histograms are formed and used for probabilistic assignment of all other pixels to the core clusters to form larger clusters and categorise the rest of the image. The process of setting up colour histograms and probabilistic reassignment of the pixels is then propagated through finer levels of smoothing until a full segmentation is achieved at the highest level of resolution.