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基于偏好免疫網(wǎng)絡(luò)的油茶果采摘機器人圖像識別算法
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林業(yè)公益性行業(yè)科研專項基金資助項目(201104090)


Camellia Fruit Image Recognition Based on Preference Artificial Immune Net
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    摘要:

    針對油茶果采摘機器人視覺識別中外界物體的形態(tài)學(xué)特性要求,采用了偏好人工免疫網(wǎng)絡(luò)算法作為機器視覺的圖像識別算法,,并根據(jù)采摘環(huán)境及采摘對象的特點對算法結(jié)構(gòu)進行了改進,,增強了算法的識別率,。仿真實驗表明,,采用偏好人工免疫網(wǎng)絡(luò)算法對油茶果的識別率在晴天時達(dá)到了81.67%,,陰天時達(dá)到了87.69%,,滿足采摘識別率的要求,。

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    With the demanding of morphological features recognition in picking robot machine-vision system, preference artificial immune net (aiNet) was used as the image recognition algorithm, mainly modified the structure of the algorithm to promote the accuracy rate. The algorithm was modified according to picking environment and real-time require. The simulation proved the clustering accuracy of preference aiNet reached to 81.67% in the sunny day and 87.69% in the cloudy day. The modified algorithm has certain meaning in the next research of picking robot.

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李立君,李昕,高自成,周健,閔淑輝.基于偏好免疫網(wǎng)絡(luò)的油茶果采摘機器人圖像識別算法[J].農(nóng)業(yè)機械學(xué)報,2012,43(11):209-213. Li Lijun, Li Xin, Gao Zicheng, Zhou Jian, Min Shuhui. Camellia Fruit Image Recognition Based on Preference Artificial Immune Net[J]. Transactions of the Chinese Society for Agricultural Machinery,2012,43(11):209-213.

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  • 在線發(fā)布日期: 2012-11-16
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