Gabor wavelets combined with volumetric fractal dimension applied to texture analysis

Autor(es)

Zuniga, Alvaro G. ^[1] ; Florindo, Joao B. ^[2] ; Bruno, Odemir M. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Math & Comp Sci, Sci Comp Grp, Sao Carlos, SP - Brazil

^[2] Univ Sao Paulo, Sao Carlos Inst Phys, Sci Comp Grp, Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PATTERN RECOGNITION LETTERS; v. 36, p. 135-143, JAN 15 2014.
• Citações Web of Science: 29

Resumo

Texture analysis and classification remain as one of the biggest challenges for the field of computer vision and pattern recognition. On this matter, Gabor wavelets has proven to be a useful technique to characterize distinctive texture patterns. However, most of the approaches used to extract descriptors of the Gabor magnitude space usually fail in representing adequately the richness of detail present into a unique feature vector. In this paper, we propose a new method to enhance the Gabor wavelets process extracting a fractal signature of the magnitude spaces. Each signature is reduced using a canonical analysis function and concatenated to form the final feature vector. Experiments were conducted on several texture image databases to prove the power and effectiveness of the proposed method. Results obtained shown that this method outperforms other early proposed method, creating a more reliable technique for texture feature extraction. (C) 2013 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