Quality assessment for agricultural products using point-cloud
| Project/Area Number |
26850165
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Agricultural environmental engineering/Agricultural information engineering
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| Research Institution | National Agriculture and Food Research Organization |
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Principal Investigator |
Yamamoto Satoshi 国立研究開発法人農業・食品産業技術総合研究機構, 農業技術革新工学研究センター総合機械化研究領域, 上級研究員 (20391526)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 三次元モデリング / ポイントクラウド / フェノタイピング / 画像処理 / 三次元センサ / 外観品質 / 三次元モデル / 内部品質 / 品質評価 / 密度 |
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| Outline of Final Research Achievements |
Three-dimensional reconstruction has great potential to improve not only the post-harvest quality control but also the breeding efficiency in horticulture. The depth information of the consumer-grade RGB-depth sensor was unreliable compared to that obtained from industrial sensors. To cope with this disadvantage, the generated point cloud was corrected within a region of interest of the target fruit, which was extracted from the color image of the sensor. Evaluating more than a hundred apple fruits, the root-mean-square error of the volume and the largest diameter were less than 6 cm3 and 1 mm, respectively. Reconstruction of various kinds of fruits and vegetables were demonstrated. The proposed method can be applied to accelerate the quantification of three-dimensional features of agricultural products.
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Report
(4 results)
Research Products
(6 results)
