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基于機器視覺的棉種破損檢測技術(shù)
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Damaged Cottonseeds Using Machine Vision
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    摘要:

    研究了破損棉種的機器視覺識別方法，采用均值、方差、均方比等統(tǒng)計特性參數(shù)，計算棉種邊界破損參數(shù)。通過實驗確定均方比分類閾值為0.58，將棉種分為破損棉種和正常棉種。選取正常棉種330粒、破損棉種110粒，利用該檢測系統(tǒng)進行檢測，其識別精度達

    Abstract:

    93%。The objective of this study is to develop image algorithms for sorting broken cottonseeds. An automatic detection system based on machine vision was designed to distinguish normal cottonseeds from broken ones. Image algorithm was developed with introduction of three statistical characteristics, which includes mean, variance and the ratio of mean to variance. Image algorithm testing on a validation data showed that broken seeds were distinguished from normal ones with accuracy of up to 93%. 

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劉韶軍,王庫.基于機器視覺的棉種破損檢測技術(shù)[J].農(nóng)業(yè)機械學報,2009,40(12):186-189. Damaged Cottonseeds Using Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(12):186-189.

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