Fractal and Multi-Scale Fractal Dimension analysis: a comparative study of Bouligand-Minkowski method
Computer Vision and Pattern Recognition
2012-01-17 v1
Abstract
Shape is one of the most important visual attributes to characterize objects, playing a important role in pattern recognition. There are various approaches to extract relevant information of a shape. An approach widely used in shape analysis is the complexity, and Fractal Dimension and Multi-Scale Fractal Dimension are both well-known methodologies to estimate it. This papers presents a comparative study between Fractal Dimension and Multi-Scale Fractal Dimension in a shape analysis context. Through experimental comparison using a shape database previously classified, both methods are compared. Different parameters configuration of each method are considered and a discussion about the results of each method is also presented.
Keywords
Cite
@article{arxiv.1201.3153,
title = {Fractal and Multi-Scale Fractal Dimension analysis: a comparative study of Bouligand-Minkowski method},
author = {André Ricardo Backes and Odemir Martinez Bruno},
journal= {arXiv preprint arXiv:1201.3153},
year = {2012}
}