Title :
Fractional box-counting approach to fractal dimension estimation
Author :
Feng, Jie ; Lin, Wei-Chung ; Chen, Chin-Tu
Author_Institution :
Dept. of Electr. & Comput. Eng., Northwestern Univ., Evanston, IL, USA
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
Keywords :
estimation theory; fractals; image classification; image segmentation; least squares approximations; base scale; counting scale; deformable box; fractal dimension estimation; fractional box-counting; image classification; image segmentation; shape analysis; Brownian motion; Character generation; Extraterrestrial measurements; Fractals; Image analysis; Image processing; Image segmentation; Image texture analysis; Radiology; Shape;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.547197
