Colour Texture Segmentation by Region-Boundary Cooperation

Abstract

A colour texture segmentation method which unifies region and boundary information is presented in this paper. The fusion of several approaches which integrate both information sources allows us to exploit the benefits of each one. We propose a segmentation method which uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation, which allow to estimate the colour behaviour, and classical co-occurrence matrix based texture features. When the region information is defined, accurate boundary information can be extracted. Afterwards, regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. In contrast with other approaches, our method achieves relevant results on images with regions with the same texture and different colour (as well as with regions with the same colour and different texture), demonstrating the performance of our proposal. Furthermore, the method has been quantitatively evaluated and compared on a set of mosaic images, and results on real images are shown and analysed.