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水稻氮素機(jī)器視覺診斷最佳葉位和位點(diǎn)的選擇研
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of Suitable Leaf for Nitrogen Diagnosis in Rice Based on Computer Vision
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    摘要:

    選用掃描儀獲取水稻葉片的數(shù)字圖像,通過比較第1和第3完全展開葉 (L1和L2) 顏色參量的空間分布,研究基于機(jī)器視覺技術(shù)的水稻氮素診斷的最佳葉位和位點(diǎn)選擇。結(jié)果表明基于機(jī)器視覺的水稻氮素營養(yǎng)診斷是有理論依據(jù)的,能反映出葉片的營養(yǎng)狀況; 選擇B、b、b/(r+g)、b/r、b/g作為最優(yōu)顏色特征參量;比較顏色特征參量對應(yīng)的變異系數(shù)CV,得到低氮處理的CV明顯高于正常氮素水平,同時CV隨著葉位的增加而減??;不同位點(diǎn)的CV其葉尖和葉基的變化幅度較為接近,不同位點(diǎn)間差異不顯著。初步研究選擇第3完全展開葉作為水稻無損氮素診斷的最佳葉位。

    Abstract:

    Prior research indicated that leaves at different positions responds differentially to the spectral characteristics under different nitrogen rates. A method based on the computer vision technology was proposed, by comparing the spatial differences of color parameters which was captured from the scanned images of upper fully expanded leaves. The result illustrated that the diagnosis of rice based on the scanned image under different N rates is able to partly reflect the hyperspectral properties. And the B、b、b/(r+g)、b/r、b/g were selected as the optimum color parameters. The coefficient of variation (CV) of the color parameters is higher at low N condition than normal. Furthermore, CV decreases with the increased leaf position. Meanwhile, the difference of CV at different part of the leaf is not obviously. The preliminary research concluded that the third fully expanded leaf can be applied as the ideal indicator to quantify the different status of nitrogen.

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祝錦霞,鄧勁松,林芬芳,王珂.水稻氮素機(jī)器視覺診斷最佳葉位和位點(diǎn)的選擇研[J].農(nóng)業(yè)機(jī)械學(xué)報,2010,41(4):179-183. of Suitable Leaf for Nitrogen Diagnosis in Rice Based on Computer Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(4):179-183.

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