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鮮食玉米果穗外觀品質(zhì)分級(jí)的計(jì)算機(jī)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(jì)算機(jī)視覺檢測(cè)技術(shù)實(shí)現(xiàn)對(duì)鮮食玉米果穗外觀品質(zhì)分級(jí),。提出垂直投影法確定禿尖位置并去除禿尖。對(duì)H值進(jìn)行雙向一次微分運(yùn)算以實(shí)現(xiàn)缺陷的識(shí)別,。在此基礎(chǔ)上獲取果穗缺陷比,、穗長(zhǎng)、果穗最大直徑,、長(zhǎng)寬比和矩形度作為外觀品質(zhì)特征參數(shù),，并以此為輸入向量構(gòu)建廣義回歸神經(jīng)網(wǎng)絡(luò)對(duì)果穗外觀品質(zhì)分級(jí)。試驗(yàn)結(jié)果表明：禿尖位置、穗長(zhǎng)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(jí)平均準(zhǔn)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(zhì)分級(jí)的計(jì)算機(jī)視覺方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),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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