Fractal and Multi-Scale Fractal Dimension analysis: a comparative study of Bouligand-Minkowski method
This is an incremental study for pattern recognition researchers, comparing existing methods without introducing new techniques.
The paper compared Fractal Dimension and Multi-Scale Fractal Dimension methods for shape analysis, finding that both were effective in estimating shape complexity through experimental tests on a classified database.
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.