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基于最小二乘法的早期作物行中心線檢測方法
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Crop Rows Detection Based on Least Square Method
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    摘要:

    提出了一種基于最小二乘法的早期作物行中心線檢測算法。利用G-R顏色特征因子分割作物與背景,。根據(jù)作物與雜草的長度屬性去除部分雜草噪聲,,應(yīng)用垂直投影法動態(tài)檢測作物行數(shù),并提取作物行中點為特征點,,獲得特征點圖像,。利用特征點間的鄰近關(guān)系對特征點進(jìn)行分類,對歸類后的特征點進(jìn)行兩次最小二乘法擬合,得到作物行中心線,。對于有作物缺失的作物行,,采用統(tǒng)計條形區(qū)域內(nèi)特征點數(shù)量的方法判別檢測結(jié)果的可信度。實驗結(jié)果表明,,算法能克服雜草和作物缺失的影響,,實時地提取小麥、玉米和大豆作物行,,平均每幅圖像處理時間小于

    Abstract:

    150ms,。To improve real-time performance of agriculture vehicle navigation, an algorithm based on least square method for detection of crop rows, especially of crops in the early stage of growth was proposed. Crops were segmented from background by the index of G-R. Parts of the noises of weeds in the image were eliminated according to their length. Crop line numbers were detected dynamically by vertical projection method. Center points of crop rows were extracted as feature points and were classified into different clusters. Least square method was used twice for fitting the center line of crop row to the feature points. The number of the feature points was counted to judge the reliability of the detection result of crop row with plant deficiency. The experimental result showed that the algorithm could overcome the effect of weed noise and plant deficiency. The average time of image processing was less than 150ms.

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司永勝,姜國權(quán),劉剛,高瑞,劉兆祥.基于最小二乘法的早期作物行中心線檢測方法[J].農(nóng)業(yè)機(jī)械學(xué)報,2010,41(7):163-167. Crop Rows Detection Based on Least Square Method[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(7):163-167.

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