2022 Fiscal Year Final Research Report
Precise 3-D remote sensing using multi-spectral image estimation and accurate 3-D reconstruction
Project/Area Number |
20K06319
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 41040:Agricultural environmental engineering and agricultural information engineering-related
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Research Institution | Toyohashi University of Technology |
Principal Investigator |
Kanazawa Yasushi 豊橋技術科学大学, 工学(系)研究科(研究院), 准教授 (50214432)
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Co-Investigator(Kenkyū-buntansha) |
小林 健一 一関工業高等専門学校, その他部局等, 講師 (80707513)
佐藤 建 一関工業高等専門学校, その他部局等, 特命助教 (70647643)
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Project Period (FY) |
2020-04-01 – 2023-03-31
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Keywords | 高精細3-Dリモートセンシング / マルチスペクトル画像推定 / 圃場3-D計測 / 糖度推定 |
Outline of Final Research Achievements |
We aimed to develop a high-precision 3-D remote sensing technology, which can assist small- and medium-scale farmers to operate their sustainable agriculture. There are three cores for doing this: (1) estimation of other single-band image from visible image, (2) easy computation or estimation of plant condition such as sugar content and vegetation index, (3) 3-D information estimation of farm field. For estimation of NIR and Red-channel image from visible image, we adopt GAN-based method; for easy estimation of sugar content, we use only visible image taken by a drone; for 3-D information of the farm, we proposed the new method that can find the difference between difference scales and ranges and we also proposed accurate depth estimation method from single image. From experiments, we find the effectiveness of our methods. In future work, we aim to establish a high-precision 3-D remote sensing using these methods.
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Free Research Field |
コンピュータビジョン,画像処理
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Academic Significance and Societal Importance of the Research Achievements |
日本に多い中小規模の農家は,働き手の高齢化だけでなく,慢性的な人手不足の問題があり,本研究で提案している高精細3-Dリモートセンシング技術に対する成果は,このような中小規模の農家に対する持続可能の農業を行える手助けと成り得ると考える.これは,比較的高価な機械の多い農家に対して,安価なドローンを導入するだけで,リモート糖度推定や圃場の状態の把握などを簡単に行えるようになるためである.
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