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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Texture classification using non-Euclidean Minkowski dilation

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Author(s):
Florindo, Joao B. [1, 2] ; Bruno, Odemir M. [1]
Total Authors: 2
Affiliation:
[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
Total Affiliations: 2
Document type: Journal article
Source: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 493, p. 189-202, MAR 1 2018.
Web of Science Citations: 2
Abstract

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)

FAPESP's process: 16/16060-0 - Pattern Recognition on Images Based on Complex Systems
Grantee:Joao Batista Florindo
Support Opportunities: Regular Research Grants
FAPESP's process: 12/19143-3 - Fractal Geometry and Image Analysis Applied to Vegetal Biology
Grantee:Joao Batista Florindo
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 14/08026-1 - Artificial vision and pattern recognition applied to vegetal plasticity
Grantee:Odemir Martinez Bruno
Support Opportunities: Regular Research Grants