Colour Texture Segmentation Using Evidence Gathering

A new approach to colour-texture segmentation is presented which uses Local Binary Pattern data and a new colour quantisation scheme based on hue and saturation to provide evidence from which pixels can be classified into texture classes. The proposed algorithm, which we contend to be the first use of evidence gathering in the field of texture classification, uses Generalised Hough Transform style R-tables as unique descriptors for each texture class. Tests on remotely sensed images demonstrate the superiority of the colour-texture algorithm compared to the established JSEG algorithm; a notable advantage of the new approach is the absence of over-segmentation. The VisTex database is used to compare the colour-texture algorithm with alternative methods, including its grey-scale equivalent, for the segmentation of colour texture images; providing good results with smooth texture boundaries and low noise within texture segments.