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蘋(píng)果采摘機(jī)器人果實(shí)識(shí)別與定位方法
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Location of Fruits for Apple Harvesting Robot
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    摘要:

    提出了利用歸一化的紅綠色差(R-G)/(R+G)分割蘋(píng)果的方法,。對(duì)不同光照情況下拍攝的蘋(píng)果圖像進(jìn)行了識(shí)別,,并對(duì)識(shí)別后的圖像進(jìn)行預(yù)處理后,,獲得蘋(píng)果的輪廓圖像,。對(duì)輪廓圖像采用隨機(jī)圓環(huán)法進(jìn)行果實(shí)圓心、半徑提取,。通過(guò)建立基于面積特征與極線(xiàn)幾何相結(jié)合的匹配策略實(shí)現(xiàn)雙目視覺(jué)下的果實(shí)定位,對(duì)于搜索區(qū)域內(nèi)面積相似的果實(shí),通過(guò)計(jì)算垂直投影的互相關(guān)函數(shù)最大值的方法,,得到排序基準(zhǔn)線(xiàn),然后根據(jù)順序一致性原則進(jìn)行匹配,。實(shí)驗(yàn)結(jié)果表明:識(shí)別算法可以較好地消除陰影,、裸露土壤等影響,識(shí)別率達(dá)到92%,。采用隨機(jī)圓環(huán)法,,可以準(zhǔn)確地提取果實(shí)的圓心、半徑,。在60~150cm的距離范圍內(nèi),,測(cè)量誤差小于

    Abstract:

    2cm。An apple recognition method with normalized color difference (R-G)/(R+G) was presented. The apples in the images taken under different lighting conditions were recognized. Some pretreatments were applied to get contour images. The shape features of the apples were extracted from the contour images based on the method of random circle ring. A matching algorithm based on area feature and epipolar geometry was discussed to position the apples. The apples with similar areas were matched according to the principle of left-right order consistency by calculating the maximum value of cross-correlation function of vertical projections. The experiments results show that the proposed recognition method can eliminate influence of shade, and soil, to a certain extent. The recognition rate reaches 92%. The circle centers and radius are extracted precisely and rapidly based on the method of random circle ring. The errors are less than 2cm when the measure distance is between 60cm and 150cm. 

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司永勝,喬軍,劉剛,高瑞,何蓓.蘋(píng)果采摘機(jī)器人果實(shí)識(shí)別與定位方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2010,41(9):148-153. Location of Fruits for Apple Harvesting Robot[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(9):148-153.

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