Fractal analysis of image textures for indexing and retrieval by content

This paper proposes the use of fractal analysis as a means to discriminate textured segmented regions of medical images. We show that the use of the fractals can boost the representation level of traditional image features allowing high rates of precision when answering similarity queries over images employing a variance weighted Manhattan distance. The cost to compute the fractal measurements is linear on the image size, what makes their use a suitable choice for large sets of images.