Potential of Texture Analysis for Charcoal Classification
Tipo de material:
ArtigoAssunto(s): Recursos online:
Em: Floresta e Ambiente (Brazil) v. 26(3) p. 1-10; (2019)Sumário:
Abstract
Charcoal produced from reforested wood can be distinguished from the charcoal derived from the
wood of native species. This identification is very important for the trade, control and monitoring
of charcoal production in Brazil. This study investigated the potential of texture analysis for
classifying the charcoal based on origin (eucalyptus or native) and species. A total of 17 wood
species were studied, five of which belonged to genus Eucalyptus and 12 were native to the Zona
da Mata Mineira. Texture features based on the gray level co-occurrence matrix were extracted
from digital images. The linear discriminant analysis was used to classify the images with these
features. Employing 10 features, 96.2% accuracy was achieved for the classification by origin
and 90.4% for the categorization by species. Texture analysis was shown to be a favorable and
effective method that could facilitate the establishment of semiautomated techniques to classify
the charcoal based on origin or species.
Keywords: discriminant analysis, gray level co-occurrence matrix, image analysis.
| Tipo de material | Biblioteca atual | Coleção | Número de chamada | Informaçaõ do volume | Situação | Devolução em | Código de barras |
|---|---|---|---|---|---|---|---|
Periódicos
|
Biblioteca Nacional de Agricultura - Binagri Agrobase - Periódicos | Periódicos agrícolas | 2019 26(3) | Online | 2025-0451 |
Publicação on-line; 33 ref.; 5 tables; 2 illus.; Summary (En)
Abstract
Charcoal produced from reforested wood can be distinguished from the charcoal derived from the
wood of native species. This identification is very important for the trade, control and monitoring
of charcoal production in Brazil. This study investigated the potential of texture analysis for
classifying the charcoal based on origin (eucalyptus or native) and species. A total of 17 wood
species were studied, five of which belonged to genus Eucalyptus and 12 were native to the Zona
da Mata Mineira. Texture features based on the gray level co-occurrence matrix were extracted
from digital images. The linear discriminant analysis was used to classify the images with these
features. Employing 10 features, 96.2% accuracy was achieved for the classification by origin
and 90.4% for the categorization by species. Texture analysis was shown to be a favorable and
effective method that could facilitate the establishment of semiautomated techniques to classify
the charcoal based on origin or species.
Keywords: discriminant analysis, gray level co-occurrence matrix, image analysis.

Periódicos
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