Texture classification using non-Euclidean Minkowski dilation

Autor(es)

Florindo, Joao B. ^{[1, 2]} ; Bruno, Odemir M. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Sao Carlos Inst Phys, Sci Comp Grp, Av Trabalhador Sao Carlense 400, BR-13560970 Sao Carlos, SP - Brazil

^[2] Univ Estadual Campinas, Inst Math Stat & Sci Comp, Rua Sergio Buarque Holanda 651, BR-13083859 Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 493, p. 189-202, MAR 1 2018.
• Citações Web of Science: 2

Resumo

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the L-p metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the L-p metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems. (C) 2017 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 16/16060-0 - Reconhecimento de padrões em imagens baseado em sistemas complexos
• Beneficiário: Joao Batista Florindo
• Linha de fomento: Auxílio à Pesquisa - Regular
• Processo FAPESP: 12/19143-3 - Geometria fractal e análise de imagens aplicadas à Biologia Vegetal
• Beneficiário: Joao Batista Florindo
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 14/08026-1 - Visão artificial e reconhecimento de padrões aplicados em plasticidade vegetal
• Beneficiário: Odemir Martinez Bruno
• Linha de fomento: Auxílio à Pesquisa - Regular