iForest - Biogeosciences and Forestry


Identification of wood from the Amazon by characteristics of Haralick and Neural Network: image segmentation and polishing of the surface

Giselly Lenise de Souza Vieira (1)   , Márcio José Moutinho da Ponte (1-2), Victor Hugo Pereira Moutinho (1), Ricardo Jardim-Gonçalves (2), Celson Pantoja Lima (1-3), Marco Valério de Albuquerque Vinagre (4)

iForest - Biogeosciences and Forestry, Volume 15, Issue 4, Pages 234-239 (2022)
doi: https://doi.org/10.3832/ifor3906-015
Published: Jul 14, 2022 - Copyright © 2022 SISEF

Research Articles

The identification of Amazonian timber species is a complex problem due to their great diversity and the lack of leaf material in the post-harvest inspection often hampers a correct recognition of the wood species. In this context, we developed a pattern recognition system of wood images to identify commonly traded species, with the aim of increasing the accuracy and efficiency of current identification methods. We used ten different species with three polishing treatments and twenty images for each wood species. As for the image recognition system, the textural segmentation associated with Haralick characteristics and classified by Artificial Neural Networks was used. We verified that the improvement of sandpaper granulometry increased the accuracy of species recognition. The developed model based on linear regression achieved a recognition rate of 94% in the training phase, and a post-training recognition rate of 65% for wood treated with 120-grit sandpaper mesh. We concluded that the wood pattern recognition model presented has the potential to correctly identify the wood species studied.


Wood Identification, Amazon, Technology, Pattern Recognition, Digital Image Processing, Artificial Neural Networks

Authors’ address

Giselly Lenise de Souza Vieira 0000-0003-0328-024X
Márcio José Moutinho da Ponte 0000-0002-0724-3721
Victor Hugo Pereira Moutinho 0000-0001-7770-3087
Celson Pantoja Lima 0000-0002-8074-8566
Graduate Program in Intellectual Property and Information Transfer Technology for Innovation/Federal University of West Pará (Brazil)
Celson Pantoja Lima 0000-0002-8074-8566
Massachusetts Institute of Technology, MA (United States of America)

Corresponding author

Giselly Lenise de Souza Vieira


de Souza Vieira GL, Moutinho da Ponte MJ, Pereira Moutinho VH, Jardim-Gonçalves R, Pantoja Lima C, de Albuquerque Vinagre MV (2022). Identification of wood from the Amazon by characteristics of Haralick and Neural Network: image segmentation and polishing of the surface. iForest 15: 234-239. - doi: 10.3832/ifor3906-015

Academic Editor

Giacomo Goli

Paper history

Received: Jun 19, 2021
Accepted: May 06, 2022

First online: Jul 14, 2022
Publication Date: Aug 31, 2022
Publication Time: 2.30 months

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