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
Abstract
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.
Keywords
Wood Identification, Amazon, Technology, Pattern Recognition, Digital Image Processing, Artificial Neural Networks
Authors’ Info
Authors’ address
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)
Ricardo Jardim-Gonçalves 0000-0002-3703-6854
Universidade Nova de Lisboa (Portugal)
Massachusetts Institute of Technology, MA (United States of America)
Corresponding author
Paper Info
Citation
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
Copyright Information
© SISEF - The Italian Society of Silviculture and Forest Ecology 2022
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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