Quality assessment for agricultural products using point-cloud

2016 Fiscal Year Final Research Report

• Project/Area Number: 26850165
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Agricultural environmental engineering/Agricultural information engineering
• Research Institution: National Agriculture and Food Research Organization
• 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)
• Project Period (FY): 2014-04-01 – 2017-03-31
• 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

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.

Free Research Field

農業環境・情報工学