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山竹的計(jì)算機(jī)視覺分級方法
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Based on Computer Vision
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    摘要:

    提出了一種基于計(jì)算機(jī)視覺技術(shù)的山竹大小和顏色分級方法,。針對以藍(lán)色滾子為背景的山竹圖像,在RGB色彩空間使用雙閾值對圖像進(jìn)行初步分割,;然后通過形態(tài)學(xué)運(yùn)算,、輪廓跟蹤、區(qū)域填充提取出整個(gè)山竹目標(biāo),;最后由顏色因子2G-R-B和G識別出果柄,、果蒂和果皮,。由果柄,、果蒂區(qū)域形心和果皮區(qū)域形心位置判斷水果的姿態(tài),,提取水果的最大橫徑作為大小分級指標(biāo);在HIS顏色空間以果皮區(qū)域的飽和度S和色調(diào)H的差值作為顏色分級指標(biāo),。選取200個(gè)山竹進(jìn)行分級試驗(yàn),,試驗(yàn)結(jié)果表明:果徑檢測精度為±1.8mm,顏色分級串級果最大比例為

    Abstract:

    10.2%,。 A grading method of mangosteen at size and color was proposed based on computer vision. Taking the blue rollers as background, the mangosteen images were pre-segmented by double thresholds in RGB color space. Through morphological operation, contour trace and region fill, the whole mangosteen target was obtained. Lastly, the peduncle, pedicel and pericarp were identified by 2G-R-B and G factors. According to the centroid of peduncle and pedicel and the centroid of pericarp, the fruit posture was evaluated, and the diameter was extracted as the size grading criteria. Meanwhile, the difference of saturation and hue of pericarp area in HIS color space was the color grading criteria. A grading experiment was carried out for 200 mangosteens. The results indicated that the accuracy of diameter measurement is ±1.8mm, and the maximal scale of neighbor grade mixed by color is 10.2%.

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張俊雄,荀一,李偉.山竹的計(jì)算機(jī)視覺分級方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2009,40(11):176-179. Based on Computer Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(11):176-179.

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