Potential of Texture Analysis for Charcoal Classification

Ano: 2019 | Volume: 26 | Número: 3

Autores: Bruno Geike de Andrade; Benedito Rocha Vital; Angélica de Cássia Oliveira Carneiro; Vanessa Maria Basso; Francisco de Assis de Carvalho Pinto

Palavras-chave: discriminant analysis; gray level co-occurrence matrix; image analysis

Resumo Inglês:

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.