本文選題：玉米葉片　切入點(diǎn)：含氮量　出處：《農(nóng)業(yè)機(jī)械學(xué)報(bào)》2017年09期

【摘要】：為了提供一種玉米葉片含氮量無(wú)損快速檢測(cè)方法,分析了玉米葉片的顏色特征參數(shù)與含氮量的關(guān)系,并基于Android手機(jī)平臺(tái)開(kāi)發(fā)了玉米葉片含氮量檢測(cè)軟件。首先獲取包含被測(cè)玉米葉片與標(biāo)定色塊組的圖像,利用標(biāo)定色塊對(duì)圖像色彩進(jìn)行校正,以減小外界光照等因素對(duì)圖像色彩造成的失真。進(jìn)而進(jìn)行圖像分割、圖像平滑和顏色特征信息提取等處理,分析了各顏色特征參數(shù)與玉米葉片含氮量的關(guān)系,發(fā)現(xiàn)綠光標(biāo)準(zhǔn)化值與含氮量之間線性關(guān)系最好。應(yīng)用Java語(yǔ)言和OpenCV計(jì)算機(jī)視覺(jué)庫(kù)在Android手機(jī)平臺(tái)上實(shí)現(xiàn)了玉米葉片的圖像獲取、圖像處理和查看結(jié)果等功能。實(shí)驗(yàn)結(jié)果表明,該方法對(duì)玉米葉片含氮量的絕對(duì)測(cè)量誤差為-0.40%~0.35%,均方根誤差為0.20%,從采集圖像到給出結(jié)果所用時(shí)間小于10 s。
[Abstract]:In order to provide a fast and nondestructive method for the detection of nitrogen content in maize leaves, the relationship between the color characteristic parameters and nitrogen content in maize leaves was analyzed. Based on the Android mobile phone platform, the detection software of nitrogen content in maize leaves is developed. Firstly, the images of maize leaves and calibration blocks are obtained, and the color of the images is corrected by the calibration color blocks. In order to reduce the distortion of image color caused by external illumination and other factors, image segmentation, image smoothing and color feature information extraction were processed, and the relationship between each color characteristic parameter and nitrogen content in maize leaf was analyzed. It is found that the linear relationship between the standard value of green light and the content of nitrogen is the best. The functions of image acquisition, image processing and viewing results of maize leaves are realized by using Java language and OpenCV computer vision library on the platform of Android mobile phone. The experimental results show that, The absolute measurement error of nitrogen content in maize leaves is -0.40 and 0.35, and the root mean square error is 0.20. The time from collecting images to giving the results is less than 10 s.
【作者單位】： 西北農(nóng)林科技大學(xué)機(jī)械與電子工程學(xué)院;
【基金】：公益性行業(yè)(農(nóng)業(yè))科研專項(xiàng)(201503137)
【分類(lèi)號(hào)】：S126;S513

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本文編號(hào)：1668241