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擾動柑橘采摘的實時識別與采摘點確定技術(shù)
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國家自然科學(xué)基金資助項目(31201135)和國家星火計劃資助項目(2013GA780043)


Real-time Identification and Picking Point Localization of Disturbance Citrus Picking
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    摘要:

    對成熟柑橘果實在擾動狀態(tài)下的視覺識別定位技術(shù)進行研究,。利用ANSYS進行了擾動柑橘的動力學(xué)分析,結(jié)合圖像處理分析結(jié)果,確定了微擾動柑橘的運動規(guī)律為類單擺運動;對采集的微擾動柑橘視頻進行圖像處理,,設(shè)定規(guī)則選取視頻中的圖像,利用改進的K-means聚類分割法結(jié)合優(yōu)化Hough圓擬合方法實現(xiàn)柑橘果實的分割,;根據(jù)圖像分割結(jié)果,,對柑橘的二值圖像進行Hough直線擬合,結(jié)合直線斜率在-0.45~0.45的約束條件,,確定擾動柑橘的有效采摘點,。試驗結(jié)果表明該方法能有效地識別自然環(huán)境中的微擾動柑橘,確定擾動果實采摘點的準(zhǔn)確率達(dá)85%,,采摘點確定的處理時間在7.58~9.24s范圍內(nèi),。

    Abstract:

    The visual identification technology of mature citrus fruits in the condition of disturbance had been studied. Firstly, analyzing disturbed citrus in ANSYS, so as to confirm the law of motion was the simple pendulum movement. Secondly, processing video image of the disturbed citrus,by using the improved K-means clustering method combined with Hough circle transform method to segment fruits. According to the image segmentation result, fitting the binary citrus image using Hough line method. With constraint of straight slope between -0.45~0.45, disturbed citrus’picking positions were determined ultimately. Test results show that this method could identify the disturbed citrus effectively in the natural environment, and the recognition rate of picking position was 85%, with processing time within 7.58s to 9.24s. The study provides the theoretical foundation and technical support for the visual localization of disturbed fruits.

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熊俊濤,鄒湘軍,彭紅星,陳文光,林桂潮.擾動柑橘采摘的實時識別與采摘點確定技術(shù)[J].農(nóng)業(yè)機械學(xué)報,2014,45(8):38-43. Xiong Juntao, Zou Xiangjun, Peng Hongxing, Chen Wenguang, Lin Guichao. Real-time Identification and Picking Point Localization of Disturbance Citrus Picking[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(8):38-43.

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  • 收稿日期:2014-03-14
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  • 在線發(fā)布日期: 2014-10-10
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