Box-Count Analysis of Two Dimensional Images: Methodology, Analysis and Classification

This paper calls attention to the methodology issues of the box-counting method, precisely, to the scaling procedure and significance of the parameter calculated for different presentation of the same image. By using basic terms of fractal analysis and statistical assessment of correlation coefficients of a straight line fit, we showed correct choice for the size of boxes. Moreover, we showed correct box-count dimension in case of neurons with sparse or thick dendrites and small or large cell bodies. In addition, this paper presents our main results relating to the quantitative study and classification of 2D images from the monkey cerebral cortex and the human caudate nucleus.