臺灣博碩士論文加值系統

本研究為本人從家中的工作中發想並實現，做分類的工人分完一籃梨子就會伸一
下腰，而且手一滑梨子常常就東滾西滾，因此原因才有了這個想法。
利用 HT66F2390 和 Halcon 影像處理軟體結合 WEBCAM，實現以影像辨識水梨等
級之水果分級機。以梨子分級過程為構想，利用相機影像辨識梨子大小，再藉由輸送
帶運輸梨子達成分級的目的。目前梨子分級方式採取重量分級的方式，整籃梨子推上
機器後機器讀取，機器讀取重量，藉由拿取梨子後，機器感應減少的重量，藉此判別
梨子等級，解決人為意外發生的水果損失和減少人力成本，進而降低果農生產時的時
間成本。
本研究預期可以減少近一半以上的人事成本支出，更可壓低 5%-10%的水果損壞
率，以水梨的採收期來說使用本研究不只能避免因人力傾向於分裝導致採收時間過
長，水梨太晚採收而過熟。原本使用語音重量分級機需要約 6 人進行分類，在使用本
研究後，可以減少到 3 人就能進行分類，剩餘的 3 人可以進行分裝或是採收，加快產
線，可以減少人力或是將人力投入其他工作中，進度加快了也能增加產量，並且結合
影像辨識技術，更進一步將傳統農業推向自動化發展。

This research was conceived and implemented by myself based on my work from home.
The workers who are involved in the sorting process tend to take a break and stretch their backs
after finishing a basket of pears. Moreover, the pears often slip from their hands and roll around,
causing difficulties. These observations led to the idea of developing a fruit grading machine
that utilizes image recognition of pear grades, using HT66F2390 microcontroller and Halcon
image processing software. The concept involves capturing camera images to identify the size
of the pears and utilizing a conveyor belt to transport the pears for grading purposes.
This research is expected to significantly reduce personnel costs by over 50% and lower
fruit damage rates by 5%-10%. Specifically, during the watermelon harvesting season, this
research not only avoids excessive harvesting time caused by manual sorting but also prevents
overripe pears due to delayed harvesting. Initially, a voice-activated weight grading machine
required approximately six people for classification. However, with the implementation of this
research, the number of personnel needed for grading can be reduced to three. The remaining
three individuals can focus on sorting or harvesting, which accelerates the production line,
reduces labor requirements, allows manpower to be allocated to other tasks, increases
productivity, and advances traditional agriculture towards automation by integrating image
recognition technology.

摘要...i
Abstract...ii
誌謝...iii
目錄...iv
表目錄...v
圖目錄...vi
第一章 緒論...1
1.1 前言...1
1.2 研究動機與目的...1
1.3 論文架構...1
第二章 文獻探討...3
2.1 農業自動化...3
2.2 影像辨識技術的應用...3
2.3 分級系統...4
第三章 研究內容與方法...5
3.1 MCU HT66F2390...5
3.2 系統架構...6
3.3 系統流程...7
3.4 傳輸方式...7
3.5 影像辨識...8
3.6 系統介面...9
3.7 電路設計...10
第四章 實驗結果與討論...13
4.1 參考值標準的建立...13
4.2 水梨等級...13
4.3 系統問題與修正...15
第五章 結論...18
5.1 結論...18
5.2 未來展望...18
參考文獻...19

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