Image segmentation by spatially adaptive color and texture features

We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more robust segmentation into texture classes. The proposed algorithm includes an elaborate border estimation procedure, which extends the idea of Pappas' adaptive clustering segmentation algorithm to color texture. The performance of the proposed algorithm is demonstrated in the domain of photographic images, including low resolution compressed images.