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Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials, Volume 33, Number 11(1) (2021)
Copyright(C) MYU K.K.
pp. 3835-3845
S&M2727 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2021.3605
Published: November 17, 2021

Computer Vision Techniques in Forest Inventory Assessment: Improving Accuracy of Tree Diameter Measurement Using Smartphone Camera and Photogrammetry [PDF]

Heesung Woo, Ikhyun Kim, and Byoungkoo Choi

(Received August 28, 2021; Accepted October 5, 2021)

Keywords: computer vision, photogrammetry, tree diameter, forest inventory, image processing

The forest industry is facing many challenges, including lack of labor and low operational efficiency. In South Korea, the small-scale forest industry has hindered the development of advanced-level forest industry due to high cost of machines and sensors. To overcome these challenges, the application of ICT technologies can be considered a means of rehabilitating the Korean forest industry. As one approach, we investigated the possibility of using smartphone-integrated computer vision in forest inventory assessment. Individual tree diameters were estimated using four different circular fitting algorithms: least-squares circle (C), minimum enclosing circle (MEC), convex hull (CH), and least-squares ellipse (E). We found that C and MEC were the most accurate algorithms for estimating the tree diameter in Pinus densiflora (PD) and Pinus koraiensis (PK) forest stands. The results of this research indicate the possibility of using smartphones to investigate the forest structure efficiently.

Corresponding author: Byoungkoo Choi


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Heesung Woo, Ikhyun Kim, and Byoungkoo Choi, Computer Vision Techniques in Forest Inventory Assessment: Improving Accuracy of Tree Diameter Measurement Using Smartphone Camera and Photogrammetry , Sens. Mater., Vol. 33, No. 11, 2021, p. 3835-3845.



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