A PDP Approach to Localized Fractal Dimension Computation with Segmentation Boundaries

Abstract

A parallel distributed processing approach to the computation of localized fractal dimension values in imagery is pre sented. This approach is a further development of the covering method which requires only nearest neighbor commu nication. A major benefit of our approach is the ability to readily incorporate any boundary information that may be available. Man y fractal textures or surfaces are fractal only in distribution. With this in mind, we show that compari son of the fractal dimension distribrctions via Kullback-Leibler can give an improved texture discrimination capability over comparison of computed fractal dimension. Results are presented for a set of textures.