Adaptive image segmentation based on color and texture

We propose an image segmentation algorithm that is based on spatially adaptive color and texture features. The features are first developed independently, and then combined to obtain an overall segmentation. Texture feature estimation requires a finite neighborhood which limits the spatial resolution of texture segmentation, while color segmentation provides accurate and precise edge localization. We combine a previously proposed adaptive clustering algorithm for color segmentation with a simple but effective texture segmentation approach to obtain an overall image segmentation. Our focus is in the domain of photographic images with an essentially unlimited range of topics. The images are assumed to be of relatively low resolution and may be degraded or compressed.