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支持向量機在斑潛蠅蟲害葉片光譜分析中的應用
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    摘要:

    測量了斑潛蠅蟲害葉片的可見光反射光譜,。運用圖像處理技術計算出蟲害葉片的破損率,;采用光譜分析方法選出對葉片破損程度敏感的波長點,。運用支持向量機(SVM)和多光譜法,,建立基于敏感波長的受害葉片反射光譜分類模型并進行分類試驗。試驗結果表明,多光譜法分類精度為90%,SVM為93.8%(多項式核函數(shù))和96.9%(RBF核函數(shù)),高于多光譜法,。

    Abstract:

    Leafminer is a vegetable insect pest. The visible spectral reflectance of the leafminer (Liriomyza sativae Blanchard) infected plant leaves was measured. Damaged degrees (DD) of leaves were worked out with the image processing technology, and the sensitive wavelengths related to them were also selected via spectroscopy analysis. Using the support vector machine (SVM) and the multi-spectral method, the spectral classifying experiments were done and the classifying models were set up to recognize the leaf spectra with different DD. The results that used the SVM and the multi-spectral methods were contrasted. The results showed that the classifying precisions of the SVM are 93.8% (using the polynomial-based kernel function) and 96.9% (using the RBF kernel function), which excelled to the multi-spectral method (whose classifying precision is 90%).

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吳達科,馬承偉,杜尚豐.支持向量機在斑潛蠅蟲害葉片光譜分析中的應用[J].農(nóng)業(yè)機械學報,2007,38(10):87-90.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(10):87-90.

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