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棉花異性纖維圖像特征提
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Feature Extraction of Cotton Foreign Fibre
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    摘要:

    針對棉花加工過程中存在的異性纖維,采用機(jī)器視覺技術(shù),通過圖像處理方法提取異性纖維目標(biāo),采集異性纖維特征數(shù)據(jù),應(yīng)用一種改進(jìn)型粗糙集理論,進(jìn)行異性纖維圖像目標(biāo)特征向量的提取,得到有效的特征向量。最后采用決策樹理論,利用提取的特征向量進(jìn)行識別,實(shí)驗(yàn)表明,所提取的特征向量對于識別棉花異性纖維是有效的,識別率達(dá)到

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    95%。 For the existence of foreign fibre during cotton processing, machine vision technology and image processing were used in order to not only extract foreign fibre goals, but also collect characteristic data of foreign fibre. Decision tree theory and feature vectors extracted were used to recognize foreign fibre after eigenvectors of aimed foreign images were effectively extracted through an improved version of rough set theory. Experimental results showed that feature vectors extracted from the image of foreign fibre for the identification of cotton foreign fibre was effective and the recognition rate reached more than 95%.

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劉雙喜,張馨,鄭文秀,王金星.棉花異性纖維圖像特征提[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2010,41(3):158-162. Feature Extraction of Cotton Foreign Fibre[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(3):158-162.

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