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基于Kinect相機的穴盤苗生長過程無損監(jiān)測方法
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江蘇省重點研發(fā)計劃項目(BE2018321),、江蘇省高等學(xué)校自然科學(xué)研究重大項目(17KJA416002),、江蘇省高校優(yōu)勢學(xué)科建設(shè)工程項目和江蘇省研究生實踐創(chuàng)新計劃項目(SJCX18-0744)


Non-destructive Monitoring of Plug Seedling Growth Process Based on Kinect Camera
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    摘要:

    為實現(xiàn)工廠化穴盤苗的無損測量,,提出一種基于Kinect相機的穴盤苗生長過程無損監(jiān)測方法,。以黃瓜穴盤苗為監(jiān)測對象,在穴盤苗正上方架設(shè)Kinect相機,,獲取穴盤苗的彩色圖像和深度圖像,,并進行彩色圖和深度圖之間的像素匹配;通過對彩色圖像進行預(yù)處理,、閾值分割,、形態(tài)學(xué)運算和連通分量統(tǒng)計,獲取穴盤發(fā)芽率,;同時,,由圖像分割獲取的幼苗輪廓和深度值計算得到葉片中心像素點坐標(biāo)及其對應(yīng)的深度,以此得到相機到幼苗葉片中心的高度,,結(jié)合相機到穴盤格的距離和穴盤高度,,實現(xiàn)對穴盤苗株高的監(jiān)測;將深度圖像進行直通濾波,、條件濾波,、邊界保持濾波處理,有效去除穴盤苗周圍的背景噪聲以及波動幅度大的深度數(shù)據(jù),,獲得幼苗葉片中像素點的有效深度,,通過在深度圖像中對葉片進行重建實現(xiàn)葉面積分析;基于獲取的穴盤苗株高和葉面積建立壯苗指數(shù)評價模型,。利用穴盤苗生長過程監(jiān)測數(shù)據(jù)進行實驗驗證,,結(jié)果表明,,在發(fā)芽后5d內(nèi),發(fā)芽率誤差不大于1.567%,;株高和實際株高之間的擬合優(yōu)度R 2 為0.875,,RMSE為1.395mm;葉面積平均誤差為2.15%,;壯苗指數(shù)擬合優(yōu)度R 2 為0.958,。說明本文設(shè)計的穴盤苗監(jiān)測方法可以實現(xiàn)對穴盤苗的發(fā)芽率、株高,、葉面積和壯苗指數(shù)的無損監(jiān)測,,為工廠化穴盤苗生長過程監(jiān)測提供了有效的解決方案。

    Abstract:

    In order to realize the non-destructive and automatic measurement of factory plug seedlings, a non-destructive monitoring method based on Kinect camera was proposed. With the cucumber plug seedlings, the Kinect camera was set up directly above the plug seedlings to obtain the depth image and the color image, and pixels matching was carried between obtained two kind of images. The germination rate was monitored by preprocessing, threshold segmentation, morphological operations and connected component statistics on color image. The center pixel point and the corresponding depth of the leaf were calculated by using the seedling contour obtained by image segmentation, and depth map, so as to obtain the height from the camera to the center of leaf. Lastly, combined with the distance of the camera to the plug tray, the seedling height of plug tray was monitored. The valid depth image was obtained by an algorithm which combined straight-through filtering, conditional filtering, and boundary-preserving filtering to effectively remove background noise around the plug seedlings and depth data with large fluctuations. Then, the leaf area was calculated by blade reconstruction. Based on the results of the height and leaf area of the plug seedling, the estimation of the healthy index was put forward. The method was verified by monitoring the growth process of plug seedlings. Within five days after germination, the monitored germination rate error was no more than 1.567%. The goodness of fit R 2 between the monitored plant height and the actual plant height was 0.875, and the RMSE was 1.395mm. The average error of the calculated leaf area was 2.15%, and the R 2 of healthy index was 0.958. The results showed that the non-destructively monitoring method for plug seedlings can provide an effective solution for the monitoring of the plug seedlings.

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王紀章,顧容榕,孫力,張運.基于Kinect相機的穴盤苗生長過程無損監(jiān)測方法[J].農(nóng)業(yè)機械學(xué)報,2021,52(2):227-235. WANG Jizhang, GU Rongrong, SUN Li, ZHANG Yun. Non-destructive Monitoring of Plug Seedling Growth Process Based on Kinect Camera[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(2):227-235.

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  • 收稿日期:2020-04-22
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  • 在線發(fā)布日期: 2021-02-10
  • 出版日期: 2021-02-10
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