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鮮食玉米果穗外觀品質分級的計算機視覺方法
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Grading for Fresh Corn Ear Using Computer Vision
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    摘要:

    在HSI顏色模型下,，通過計算機視覺檢測技術實現(xiàn)對鮮食玉米果穗外觀品質分級,。提出垂直投影法確定禿尖位置并去除禿尖,。對H值進行雙向一次微分運算以實現(xiàn)缺陷的識別,。在此基礎上獲取果穗缺陷比,、穗長,、果穗最大直徑,、長寬比和矩形度作為外觀品質特征參數,，并以此為輸入向量構建廣義回歸神經網絡對果穗外觀品質分級,。試驗結果表明：禿尖位置,、穗長和果穗最大直徑的平均誤差分別為2.27mm、1.96mm和0.54mm,，缺陷誤判率為3.00%,，分級平均準確率為

    Abstract:

    95.91%。Appearance quality grading for fresh corn ear was implemented by computer vision based on HSI color model. Bare tip position was detected and removed using projection method. Defects of fresh corn ear were identified by the first order differential operation on H. Characteristic parameters of appearance quality, such as defect proportion, ear length, ear maximum diameter, aspect ratio and rectangle factor were obtained. General regression neural network with five characteristic parameters as input was developed for grading. Experiment showed that average errors of bare tip position, ear length and ear maximum diameter were 2.27mm, 1.96mm and 0.54mm, respectively. Mistake rate of defect proportion was 3.00%, and grading average ratio was up to 95.91%.

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王慧慧,孫永海,張婷婷,張貴林,李義,劉鐵鵬.鮮食玉米果穗外觀品質分級的計算機視覺方法[J].農業(yè)機械學報,2010,41(8):156-159. Grading for Fresh Corn Ear Using Computer Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(8):156-159.

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