Fractional box-counting approach to fractal dimension estimation

Abstract

The estimation of the fractal dimension is essential in fractal-based image segmentation, classification and shape analysis. The most popular estimation approach is based on box-counting. However, the partition and counting methods used in the regular box-counting scheme produces inaccurate results. In this paper, a more accurate fractional box-counting approach is proposed to estimate the fractal dimension in an image. By separating the concepts of base scale and counting scale, the new approach is able to use a deformable box to capture fractal property at some predetermined resolution. Preliminary results using the fractional box-counting approach have demonstrated that it is an accurate and efficient method.