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基于色度和紋理的黃瓜霜霉病識(shí)別與特征提取
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國(guó)家高技術(shù)研究發(fā)展計(jì)劃(863計(jì)劃)資助項(xiàng)目（2008AA100905、2007AA04Z222）,、高等學(xué)校博士學(xué)科點(diǎn)專項(xiàng)科研基金資助項(xiàng)目（200800191014）,、中國(guó)農(nóng)業(yè)大學(xué)科研啟動(dòng)基金資助項(xiàng)目(2007027) 和中國(guó)農(nóng)業(yè)大學(xué)基本科研業(yè)務(wù)費(fèi)研究生科研創(chuàng)新專項(xiàng)


Recognition and Features Extraction of Cucumber Downy Mildew Based on Color and Texture
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    摘要:

    研究了可見光波段的黃瓜霜霉病信息分布和分割方法,，有效實(shí)現(xiàn)了溫室非結(jié)構(gòu)環(huán)境下黃瓜病害信息識(shí)別,。通過研究溫室黃瓜圖像在RGB,、HIS和YCbCr顏色空間的分布特點(diǎn),，建立了光照分析模型,，提高了不同光照條件下的病害提取適應(yīng)性。分析了病害目標(biāo)與環(huán)境背景Cb和Cr均值差,，提出了CbCr組合算法,，實(shí)現(xiàn)了目標(biāo)的快速有效識(shí)別，滿足了實(shí)時(shí)對(duì)靶施藥的要求,。通過隨機(jī)抽取30幅黃瓜霜霉病圖像進(jìn)行算法驗(yàn)證,，結(jié)果表明圖像的平均識(shí)別正確率達(dá)90.6%。

    Abstract:

    An extraction algorithm based on color and texture was developed to realize segmentation between downy mildew and cucumber plants in greenhouse. A light analysis model was established by comparing the distribution of cucumber images in RGB, HIS and YCbCr color space, which was beneficial to the recognition of disease in variable illuminations. Combination model of Cband Cr elements was built based on the mean difference of lesions and interference informations in Cb and Cr, which included leaves, poles and soil, and extracted target rapidly. A detecting expriment was carried out on 30 images with downy mildew, which were taken in a changing greenhouse enviornment. The results indicated that the accuracy rate of segmentation was 90.6%. 

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耿長(zhǎng)興,張俊雄,曹崢勇,李偉.基于色度和紋理的黃瓜霜霉病識(shí)別與特征提取[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2011,42(3):170-174. Geng Changxing, Zhang Junxiong, Cao Zhengyong, Li Wei. Recognition and Features Extraction of Cucumber Downy Mildew Based on Color and Texture[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(3):170-174.

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