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機器視覺應用在魚苗計數之可行性研究

The Feasible Study of Applying Machine Vision Technique to Minnows-Counting

摘要


本文在此研究機器視覺系統應用在魚苗計數之可行性技術,研究重點在探討精確計數魚苗的影像處理方法。文中採用較低成本的視覺系統,配合撰寫高效率的影像處理軟體,使能滿足線上計數作業的要求,影像處理所採用的方法與流程爲:影像凍結→二值化→開運算→閉運算→遞迴計數。試驗結果得知碗盤內魚苗在70隻內,計數準確率可達99%以上,所花的計算時間約3秒。

並列摘要


This paper studies the feasibility of applying machine vision technique to minnows-counting. The content of the present study is focused on the exploration of image processing method. Also, the cost-effective machine vision system associated with programming a high efficient software of image processing is developed to meet the requirement of on-line operation. The steps of image processing methods for accurately counting minnows is: Freezing image→Binarying image→Opening operator→Closing operator→Counting minnows by recursive method. The results of testing indicate that the accuracy of counting minnows approaches above 99% as the numbers of minnows in shallow bowl is less than 70 numbers. The overall computational time of image processing for the present program requires about 3 seconds.

被引用紀錄


陳宸効(2009)。介電泳型生物晶片檢測儀光學模擬與性能分析〔碩士論文,國立屏東科技大學〕。華藝線上圖書館。https://doi.org/10.6346/NPUST.2009.00200
鍾昌翰(2012)。影像處理技術應用於河床粒徑分析及魚類數量調查〔博士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2012.00293
蕭友晉(2006)。以混合高斯理論影像計數浮萍與魚類族群之研究〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2006.00126
陳秀如、陳佐民、葉期財、陳銘志(2022)。整合物聯網與雲端計算的智慧數蝦應用管理資訊計算11(2),155-164。https://doi.org/10.6285/MIC.202209_11(2).0012

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