02188nab a2200301 i 4500003000900000005001700009008004100026040001800067072001400085072000800099100002800107100002700135100004700162100002500209100004300234245006200277500007000339520109900409650001301508650001401521650002101535650001201556650002001568773019001588856008101778942000801859999001901867BR-BrBNA20260402122433.0260402b2019    bl.qr|pooa||| 00| 0 eng |  aBR-BrBNAbeng  aP06b8905  aP07  aAndrade, Bruno Geike de  aVital, Benedito Rocha   aCarneiro, Angélica de Cássia Oliveira   aBasso, Vanessa Maria  aPinto, Francisco de Assis de Carvalho   aPotential of Texture Analysis for Charcoal Classification  aPublicação on-line; 33 ref.; 5 tables; 2 illus.; Summary (En)  a

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.  aCARVÃO  aANÁLISE  aESPÉCIE NATIVA  aMADEIRA  aREFLORESCIMENTO0 029299347952dRio de Janeiro-RJ Instituto de Florestas - UFRRJ 1994o2025-0451tFloresta e Ambiente (Brazil)x1415-0980  /  ISSN 2179-8087 0nlinegv. 26(3) p. 1-10; (2019)wBR2026000262  uhttps://www.scielo.br/j/floram/a/X4bWXJt6SLzhWNnD7vT6WWb/?format=pdf&lang=en  cANA  c341214d341214