Fractal and Multi-Scale Fractal Dimension analysis: a comparative study of Bouligand-Minkowski method

Shape is one of the most important visual attributes used 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-Sc...

Descripción completa

Detalles Bibliográficos
Autores: Backes, André Ricardo, Bruno, Odemir Martinez
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2008
País:Brasil
Institución:Universidade Federal de Lavras (UFLA)
Repositorio:INFOCOMP: Jornal de Ciência da Computação
Idioma:inglés
OAI Identifier:oai:infocomp.dcc.ufla.br:article/220
Acceso en línea:https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/220
Access Level:acceso abierto
Palabra clave:Complexity
Shape Analysis
Fractal Dimension
Multi-Scale Fractal Dimension
Fourier Transform
Descripción
Sumario:Shape is one of the most important visual attributes used 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.