A New Box-Counting Method for Estimation of Image Fractal Dimension

Author

Jian Li ; Caixin Sun ; Qian Du

Author_Institution

Key Lab. of High Voltage & New Electr. Technol., Chongqing Univ., China

fYear

2006

Firstpage

3029

Lastpage

3032

Abstract

Fractal dimension (FD) is an effective measure for complex objects. It is widely applied in the fields of image segmentation and shape recognition. This paper presents a new box-counting method for estimation of fractal dimension of images. Original ideas of the method came from the principles of differential box-counting (DBC) method. Improvements appear in the approach on partition of image plane and computation of the number of boxes covering the image. The computation results of fractal dimension of simulated images and Brodatz texture images demonstrate the new method is effective and produces a wider range in fractal dimension than the original DBC method.

Keywords

fractals; image classification; image segmentation; image texture; Brodatz texture images; DBC; FD; differential box-counting method; image classification; image fractal dimension estimation; image segmentation; shape recognition; simulated images; Computer science education; Educational technology; Fractals; Image recognition; Image segmentation; Laboratories; Shape; State estimation; Sun; Voltage; Image segmentation; image classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2006 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1522-4880

Print_ISBN

1-4244-0480-0

Type

conf

DOI

10.1109/ICIP.2006.313005

Filename

4107208