Unsupervised color image segmentation based on local fractal descriptor and J-images

This paper proposes an improved version for the JSEG color image segmentation algorithm, combining the classical JSEG algorithm and a local fractal operator that measures the fractal dimension of each pixel, thus improving the boundary detection in the J-map. Experiments with natural color images of the Berkeley Segmentation Dataset and Benchmark are presented, which show improved results in comparison with the classical JSEG algorithm.