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Development of YOLO-based apple quality sorter

  • Donggun Lee (Department of Bio-industrial Engineering, Kyungpook National University) ;
  • Jooseon Oh (Department of Convergence Biosystems Engineering, Chonnam National University) ;
  • Youngtae Choi (Department of Bio-industrial Engineering, Kyungpook National University) ;
  • Donggeon Lee (Department of Bio-industrial Engineering, Kyungpook National University) ;
  • Hongjeong Lee (Department of Bio-industrial Engineering, Kyungpook National University) ;
  • Sung-Bo Shim (Department of Bio-industrial Engineering, Kyungpook National University) ;
  • Yushin Ha (Department of Bio-industrial Engineering, Kyungpook National University)
  • 투고 : 2023.04.24
  • 심사 : 2023.07.10
  • 발행 : 2023.09.01

초록

The task of sorting and excluding blemished apples and others that lack commercial appeal is currently performed manually by human eye sorting, which not only causes musculoskeletal disorders in workers but also requires a significant amount of time and labor. In this study, an automated apple-sorting machine was developed to prevent musculoskeletal disorders in apple production workers and to streamline the process of sorting blemished and non-marketable apples from the better quality fruit. The apple-sorting machine is composed of an arm-rest, a main body, and a height-adjustable part, and uses object detection through a machine learning technology called 'You Only Look Once (YOLO)' to sort the apples. The machine was initially trained using apple image data, RoboFlow, and Google Colab, and the resulting images were analyzed using Jetson Nano. An algorithm was developed to link the Jetson Nano outputs and the conveyor belt to classify the analyzed apple images. This apple-sorting machine can immediately sort and exclude apples with surface defects, thereby reducing the time needed to sort the fruit and, accordingly, achieving cuts in labor costs. Furthermore, the apple-sorting machine can produce uniform quality sorting with a high level of accuracy compared with the subjective judgment of manual sorting by eye. This is expected to improve the productivity of apple growing operations and increase profitability.

키워드

과제정보

본 연구는 농림축산식품부와 농림식품기술기획평가원의 "전기구동 사료작물 수확기 플랫폼 설계 검증 및 최적화(2/4)"의 지원을 받아 수행된 연구 결과입니다 (No. 322045-04).

참고문헌

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