Fractional box-counting approach to fractal dimension estimation

Jie Feng, Wei Chung Lin*, Chin Tu Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

46 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationTrack B
Subtitle of host publicationPattern Recognition and Signal Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages854-858
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
StatePublished - Jan 1 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: Aug 25 1996Aug 29 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
Country/TerritoryAustria
CityVienna
Period8/25/968/29/96

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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