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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Using down-sampling for multiscale analysis of texture images

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Autor(es):
Silva, Pedro M. [1, 2] ; Florindo, Joao B. [1]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Univ Camp Nas, Inst Math Stat & Sci Comp, Rua Sergio Buarque Holanda 651, BR-13083859 Campinas, SP - Brazil
[2] Fed Inst Educ Sci & Technol Espirito Santo, Rodovia Governador Jose Sete 184, BR-29150410 Cariacica, ES - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: PATTERN RECOGNITION LETTERS; v. 125, p. 411-417, JUL 1 2019.
Citações Web of Science: 0
Resumo

This work proposes the study of a simple yet efficient strategy to accomplish multiscale analysis of gray level images. The method is applied to the classification of texture/material images. The proposal employs histograms of down-sampled versions of the initial image to compose a feature vector. A statistical model based on Markov random fields is also developed and employed to explain how the information conveyed by the proposed descriptors can express degrees of homo/heterogeneity in the image. This is widely known to be a fundamental feature in texture analysis. The accuracy of our descriptors is compared to several state-of-the-art approaches and the achieved results confirm our expectation that a straightforward method can be efficiently employed even in the recognition of objects in large and complex databases. (C) 2019 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