基于偏好免疫网络的油茶果采摘机器人图像识别算法
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林业公益性行业科研专项基金资助项目(201104090)


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

    针对油茶果采摘机器人视觉识别中外界物体的形态学特性要求,采用了偏好人工免疫网络算法作为机器视觉的图像识别算法,并根据采摘环境及采摘对象的特点对算法结构进行了改进,增强了算法的识别率。仿真实验表明,采用偏好人工免疫网络算法对油茶果的识别率在晴天时达到了81.67%,阴天时达到了87.69%,满足采摘识别率的要求。

    Abstract:

    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,闵淑辉.基于偏好免疫网络的油茶果采摘机器人图像识别算法[J].农业机械学报,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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  • 在线发布日期: 2012-11-16
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