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基于機器視覺的自然環(huán)境中獼猴桃識別與特征提取
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國家自然科學(xué)基金資助項目(61175099);西北農(nóng)林科技大學(xué)人才基金資助項目(Z111020902)


Recognition and Feature Extraction of Kiwifruit in Natural Environment Based on Machine Vision
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    摘要:

    研究了綜合應(yīng)用果實顏色和形狀特征識別自然環(huán)境中獼猴桃果實及特征提取的方法,。通過對比不同顏色空間,選用R—G色差分量,;再采用基于誤分割像素的分割評價方法來確定顏色特征nR—G中最佳分割系數(shù)n,,最終選取0.9R—G顏色特征,。利用Otsu法對其進行閾值分割,,形態(tài)學(xué)運算去除掉殘余噪聲,,實現(xiàn)了目標(biāo)果實區(qū)域和背景區(qū)域的分割,。然后利用Canny算子提取邊界,,最后對邊界圖像進行橢圓形Hough變換,,逐個識別出目標(biāo)果實,并提取出果實的形心坐標(biāo),、長軸端點坐標(biāo)和長短軸長度等特征信息,。對49幅包含110個果實圖像進行識別試驗,試驗結(jié)果表明:相互分離果實的識別率為96.9%,,鄰接果實識別率為92.0%,,被枝葉部分遮擋果實識別率為86.6%,重疊的果實識別率為81.6%,。

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    A method for fruit recognition and feature extraction based on the color and shape features of kiwifruit in nature was studied. It could reduce the influences of complicated background, different kiwi growth state and natural lighting condition. First, R—G color component was chosen by comparing different color spaces. Then the optimum partition coefficient of nR—G color characteristics was determined according to the image evaluation method of error segmentation pixel, and 0.9R—G was selected finally. The Otsu method was used for threshold segmentation and morphological operation was employed to remove residual noise, and then the regions of target fruits and backgrounds were successfully separated. The image boundary was extracted by Canny operator and consequent elliptic Hough transform, which made the target fruit be recognized separately. Also, fruit features as centroid coordinates, long axis end coordinates, long axis length and short axis length were extracted. By using this method, 49 images including 110 fruits were tested. Test results demonstrated that the recognition ratio of separate fruit, adjacency fruit, partial sheltering fruit and overlapped fruit were 96.9%, 92.0%, 86.6% and 81.6%, respectively.

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崔永杰,蘇帥,王霞霞,田玉鳳,李平平,張發(fā)年.基于機器視覺的自然環(huán)境中獼猴桃識別與特征提取[J].農(nóng)業(yè)機械學(xué)報,2013,44(5):247-252. Cui Yongjie, Su Shuai, Wang Xiaxia, Tian Yufeng, Li Pingping, Zhang Fanian. Recognition and Feature Extraction of Kiwifruit in Natural Environment Based on Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(5):247-252.

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  • 在線發(fā)布日期: 2013-04-28
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