Local fractal dimension and binary patterns in texture recognition

Autor(es)

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

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Sao Carlos Inst Phys, POB 369, BR-13560970 Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PATTERN RECOGNITION LETTERS; v. 78, p. 22-27, JUL 15 2016.
• Citações Web of Science: 7

Resumo

The present work proposes a new texture image descriptor, combining the local binary patterns extracted from the grey-level image (classic approach) with those extracted from the local fractal dimension at each point of the image. In this way, these descriptors express two important measurements from the image, i. e., the variation among pixel intensities in each local neighbourhood and the local complexity (pixel arrangement) at each point. Such combination provides a rich and robust descriptor even for the most complex textures. The effectiveness of the proposed solution is evaluated in the classification of two well-known benchmark databases: UIUC and USPTex, showing that the combined features outperform all the other compared approaches in terms of correctness rates in the classification of grey-scale texture images. (C) 2016 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 11/01523-1 - Métodos de visão computacional aplicados à identificação e análise de plantas
• Beneficiário: Odemir Martinez Bruno
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 12/19143-3 - Geometria Fractal e Análise de Imagens Aplicadas à Biologia Vegetal
• Beneficiário: Joao Batista Florindo
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado