  Texture plays an important role in computer vision. It is one of the most
important visual attributes used in image analysis, once it provides
information about pixel organization at different regions of the image. This
paper presents a novel approach for texture characterization, based on
complexity analysis. The proposed approach expands the idea of the Mass-radius
fractal dimension, a method originally developed for shape analysis, to a set
of coordinates in 3D-space that represents the texture under analysis in a
signature able to characterize efficiently different texture classes in terms
of complexity. An experiment using images from the Brodatz album illustrates
the method performance.
