A5040340179- Remote Sensing and LiDAR Applications
- Plant Pathogens and Fungal Diseases
- Remote Sensing in Agriculture
- 3D Surveying and Cultural Heritage
- Leaf Properties and Growth Measurement
- Plant Physiology and Cultivation Studies
- Soil and Land Suitability Analysis
- Agriculture, Soil, Plant Science
- Industrial Vision Systems and Defect Detection
- Horticultural and Viticultural Research
- Species Distribution and Climate Change
- Color Science and Applications
- Greenhouse Technology and Climate Control
- Textile materials and evaluations
Tokyo University of Agriculture and Technology
2022-2024
The quality of radish roots depends largely on its cultivar, production environment, and postharvest management along the supply chain. Quality monitoring fresh products is utmost importance during period. purpose this study to nondestructively estimate weight a using random forests based color shape information obtained from images, as well volumetric by analyzing point cloud combining multiple forms information. explanatory variables were through an image analysis still images radishes...
This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. Radish leaf patches 1.5 cm diameter were photographed halogen or LED light. The input variables for prediction using random forests RGB values, HSL and HSV values. Additionally, color temperature (LCT) illuminance (ILL) used as variables. Model performance was assessed Pearson’s correlation coefficient (COR), Nash-Sutcliffe efficiency (NSE), root...
This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. The input variables for prediction using Random Forests, XGBoost, and LightGBM were RGB values, HSL HSV color temperature (LCT), illuminance (ILL). Model performance was assessed Pearson’s correlation coefficient (COR), Nash–Sutcliffe efficiency (NSE), root mean squared error (RMSE). Especially, with Forests resulted in high accuracy a stable environment;...
ハツカダイコンの品質は,品種に大きく依存するが,青果物の品質は生産環境とポストハーベスト管理によって決定される.特に,ポストハーベスト管理のためには品質モニタリングが重要である.そこで本研究は,ランダムフォレストを用いて,画像から得られる色情報と形状情報に基づいて,非破壊でハツカダイコンの品質を推定することを目的とした.説明変数である色情報と形状情報は,一定の撮影環境下でハツカダイコンの静止画像を撮影し,画像解析により取得した.実験の結果,色情報と形状情報を用いたモデルの再現性が良好であったことから,色情報および形状情報とハツカダイコンの重量の関係性に基づいて,非破壊でのモニタリングができる可能性が示唆された.本研究で対象としたハツカダイコンは,赤系品種であったため,色情報の中でもR値が重要な変数であった.この色情報は撮影環境に変化のない条件で取得した色情報であるため,屋外や太陽光の影響がある室内環境などで撮影された画像を用いる場合に関する検討が必要である.また,本研究の成果は,特定品種に依存する研究成果ではあるものの,品種ごとにモデルを構築することで内部品質が推定できる可能性が...
This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. Radish leaf patches 1.5 cm diameter were photographed halogen or LED light. The input variables for prediction using random forests RGB values, HSL and HSV values. Additionally, color temperature (LCT) illuminance (ILL) used as variables. Model performance was assessed Pearson’s correlation coefficient (COR), Nash-Sutcliffe efficiency (NSE), root mean...
Plant growth is one of the most important components in production environment control. In recent years, development stereo imaging techniques and, hardware such as camera allows for precise measurement 3D structure an object. However, order to monitor plant at multiple points space and time, it necessary construct affordable system from a practical viewpoint agriculture. Therefore, this study, we focus on parameter optimization parallax estimation achieve highly accurate height even with...