Gabor wavelets combined with volumetric fractal dimension applied to texture analysis

Author(s)

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

Affiliation

^[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

• Document type: Journal article
• Source: PATTERN RECOGNITION LETTERS; v. 36, p. 135-143, JAN 15 2014.
• Web of Science Citations: 29

Abstract

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)

• FAPESP's process: 11/01523-1 - Computer vision methods applied to the identification and analysis of plants
• Grantee: Odemir Martinez Bruno
• 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