Development of Green Soybean-Sorting Method Using Image Processing (Part 1)

  • KATAHIRA Mitsuhiko
    The Japanese Society of Agricultural Machinery Akita Prefectural Agriculture, Forestry and Fisheries Research Center
  • TAMURA Akira
    Akita Prefectural Agriculture, Forestry and Fisheries Research Center, Agricultural Experiment Station
  • ZHAN Shu-huai
    The Japanese Society of Agricultural Machinery Faculty of Agriculture and Life Science, Hirosaki University
  • OHIZUMI Takahiro
    Yamamoto Co., Ltd.
  • GOTOU Tsu-neyoshi
    Yamamoto Co., Ltd.

Bibliographic Information

Other Title
  • 画像処理によるエダマメの選別方法に関する研究 (第1報)
  • ガゾウ ショリ ニ ヨル エダマメ ノ センベツ ホウホウ ニ カンスル ケンキュウ ダイ 1ポウ シュヨウ ショウガイ ノ ブンルイ ト センベツ キジュン ノ サクテイ
  • Damage Classification and Determination of a Sorting Standard
  • 主要傷害の分類と選別基準の策定

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Abstract

This study investigated sorting points and sorting grades to facilitate the development of a green soybean-sorting machine using image processing. For green soybeans harvested at the optimal time, 36-44% of the pods were classified outside the grade. Of those, 6-15% showed mechanical damage. We classified the mechanical damage into types I-V. Furthermore, we classified the sorting points for shape damage, damage due to green soybean seed maturity, damage due to pests, and mechanical damage. Among those points, pest damage and mechanical damage (type I, type II, type V) that produced color change points in the pods were classified according to the ratio of damaged areas to total pod area. Therefore, grade A was less than 10%, grade B was 10-15%, and outside grade (substandard) was greater than 15%.

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