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基于D—S證據(jù)理論的決策級多特征融合蘋果分級方法
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鹽城工學(xué)院重點(diǎn)建設(shè)學(xué)科開放基金資助項(xiàng)目(XKY2010021)


Multi-feature Decision Fusion Method Based on D—S Evidence Theory for Apple Grading
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    針對單特征蘋果分級的不確定性和低正確率,,通過圖像處理提取大小,、形狀、顏色和缺陷4類能反映蘋果外觀品質(zhì)的主要特征,引入信息融合的思想,,以單特征初步分級的結(jié)果作為證據(jù),,用D—S證據(jù)理論的方法進(jìn)行決策級融合處理,實(shí)現(xiàn)蘋果的多特征綜合分級,,進(jìn)一步提高可靠性和分級正確率,。80個(gè)測試樣本的分級試驗(yàn)表明,蘋果分級正確率達(dá)92.5%,,與單特征分級相比,,此方法正確識(shí)別率高、穩(wěn)定性好,、效果顯著,。

    Abstract:

    According to the uncertainty and low accuracy of apple grading relying on the single feature, key features such as size, shape, color and defect which could show the apples appearance quality were extracted and a decision fusion method based on D—S evidence theory was proposed. Firstly, the apples were graded according to each of the four features utilizing human experience and neural network. Then, the former grading results were used as evidences to achieve the decision fusion in order to increase the grading reliability and accuracy. Finally, 80 apple samples were used to test grading effect. The experimental results showed that five apples were misjudged and the grading accuracy reached to 92.5%. The proposed method had good performance on classification rate and stability compared to the grading method based on single feature. 

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李先鋒,朱偉興,花小朋,孔令東.基于D—S證據(jù)理論的決策級多特征融合蘋果分級方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2011,42(6):188-192. Li Xianfeng, Zhu Weixing, Hua Xiaopeng, Kong Lingdong. Multi-feature Decision Fusion Method Based on D—S Evidence Theory for Apple Grading[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(6):188-192.

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