Combining fractal and deterministic walkers for texture analysis and classification

Autor(es)

Goncalves, Wesley Nunes ^[1] ; Bruno, Odemir Martinez ^[1]

Afiliação do(s) autor(es)

^[1] Univ Fed Sao Carlos, Sao Carlos Inst Phys IFSC, Sci Comp Grp, BR-13560970 Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PATTERN RECOGNITION; v. 46, n. 11, p. 2953-2968, NOV 2013.
• Citações Web of Science: 14

Resumo

In this paper, we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets. (C) 2013 Elsevier Ltd. 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: 10/08614-0 - Análise de Texturas Estáticas e Dinâmicas e suas Aplicações em Biologia e Nanotecnologia
• Beneficiário: Wesley Nunes Gonçalves
• Modalidade de apoio: Bolsas no Brasil - Doutorado