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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Feature extraction on local jet space for texture classification

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Author(s):
da Silva Oliveira, Marcos William [1, 2] ; da Silva, Nubia Rosa [1, 2] ; Manzanera, Antoine [3] ; Bruno, Odernir Martinez [1, 2]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, USP, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Sao Carlos Inst Phys, Sci Comp Grp, BR-13566590 Sao Carlos, SP - Brazil
[3] Univ Paris Saclay, ENSTA ParisTech, Robot & Vis U2IS, F-91762 Palaiseau - France
Total Affiliations: 3
Document type: Journal article
Source: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 439, p. 160-170, DEC 1 2015.
Web of Science Citations: 7
Abstract

The proposal of this study is to analyze the texture pattern recognition over the local jet space looking forward to improve the texture characterization. Local jets decompose the image based on partial derivatives allowing the texture feature extraction be exploited in different levels of geometrical structures. Each local jet component evidences a different local pattern, such as, flat regions, directional variations and concavity or convexity. Subsequently, a texture descriptor is used to extract features from 0th, 1st and 2nd-derivative components. Four well-known databases (Brodatz, Vistex, Usptex and Outex) and four texture descriptors (Fourier descriptors, Gabor filters, Local Binary Pattern and Local Binary Pattern Variance) were used to validate the idea, showing in most cases an increase of the success rates. (C) 2015 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 type: Regular Research Grants
FAPESP's process: 11/21467-9 - Heterogeneous pattern recognition and its applications in biology and nanotechnology
Grantee:Núbia Rosa da Silva
Support type: Scholarships in Brazil - Doctorate