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基于色調(diào)分形維數(shù)的柑橘糖度和有效酸度檢
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Content and the Valid Acidity Test of the Citrus Based on the Fractal Dimensions of Hue
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    摘要:

    研究了宮川溫州蜜柑糖度及有效酸度的機器視覺檢測技術(shù)及影響檢測精度的因素,。對機器視覺系統(tǒng)采集的柑橘圖像進行圖像裁切、亮度法去圖像背景和RGB空間至HSI空間的轉(zhuǎn)換,,將柑橘色調(diào)范圍分割為0°~20°,、20°~40°、40°~60°,、60°~80°,、80°~100°和100°~120°共6個區(qū)域,提取各區(qū)域色調(diào)分形維數(shù),,以此作為BP神經(jīng)網(wǎng)絡(luò)輸入,,無損檢測宮川溫州蜜柑糖度及有效酸度。167個測試樣本的檢測結(jié)果表明:在±1.5°Brix精度范圍內(nèi)糖度正確識別率為66.6175%,,在±0.5精度范圍內(nèi)有效酸度正確識別率為73.9275%,。宮川溫州蜜柑糖度及有效酸度與果皮色調(diào)分形維數(shù)之間具有相關(guān)性,可用機器視覺檢測其糖度及有效酸度。

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    Non-destructive detection methods of sugar content and valid acidity of Gongchuan Wenzhou citrus fruits were investigated based on computer vision. Factors which influenced the accuracy of detection were studied. Citrus fruit images from computer vision system were cut, the background was removed and conversion from RGB to HSI space was made. These images were segmented according to hue value ranges which are 0°~20°, 20°~40°, 40°~60°, 60°~80°, 80°~100° and 100°~120° hue. Fractal dimensions of each segment were calculated as inputs of BP neural network which modeled sugar content and valid acidity of citrus fruits. Results of 167 test samples showed the correctness for accuracy ±1.5°Brix of sugar content is 66.6175%, for valid acidity, the correctness for accuracy ±0.5 is 73.9275%. From these results it concluded that sugar content and valid acidity of Gongchuan Wenzhou citrus fruits has significant correlation with fractal dimension of hue value of fruit pericarp. Computer vision can be utilized to non-destructively detect these two parameters.

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曹樂平,溫芝元,沈陸明.基于色調(diào)分形維數(shù)的柑橘糖度和有效酸度檢[J].農(nóng)業(yè)機械學(xué)報,2010,41(3):143-148. Content and the Valid Acidity Test of the Citrus Based on the Fractal Dimensions of Hue[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(3):143-148.

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