A simplified gravitational model to analyze texture roughness

Authors:
Jarbas Joaci De Mesquita Sá Junior;André Ricardo Backes
Affiliations:
Departamento de Engenharia de Teleinformática-DETI, Centro de Tecnologia-UFC, Campus do Pici, S/N, Bloco 725, Caixa Postal 6007, CEP: 60.455-970, Fortaleza, Brasil;Faculdade de Computação, Universidade Federal de Uberlíndia, Av. João Naves de Ávila, 2121, 38408-100, Uberlíndia, MG, Brasil
Venue:
Pattern Recognition
Year:
2012

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Abstract

Textures are among the most important visual attributes in image analysis. This paper presents a novel method to analyze texture, based on representing states of a simplified gravitational collapse from an image and extracting information from each state using fractal dimension. In this approach, an image evolves in times t={1,2,...,20}, each time representing a state, which is explored by the Bouligand-Minkowski method using radius r={3,4,...,8}. These parameters allow to create a set of feature vectors, which were extracted from Brodatz's textures and leaf textures. The best classification results were 98.75% and 86.67% of success rate (percentage of samples correctly classified) for these two databases, respectively. These results prove that the proposed approach opens a promising source of research in texture analysis to be explored.