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Journal of Chinese Agricultural Mechanization

Journal of Chinese Agricultural Mechanization ›› 2021, Vol. 42 ›› Issue (9): 187-194.DOI: 10.13733/j.jcam.issn.2095-5553.2021.09.26

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A method of Camellia fruit sorting based on multifeatures identification in preference aiNet

Li Xin, Chen Zejun, Li Lijun, Tan Jiqiu, Wu Fazhan. #br#   

  • Online:2021-09-15 Published:2021-09-15

一种基于偏好免疫网络多特征辨识的油茶果分选识别方法

李昕;陈泽君;李立君;谭季秋;吴发展;   

  1. 湖南工程学院机械工程学院;湖南省林业科学院;中南林业科技大学机电工程学院;株洲丰科林业装备科技有限责任公司;
  • 基金资助:
    国家重点研发计划项目(2016YFD0702100)
    湖南省重点研发计划项目(2018NK2065)

Abstract: In order to solve the problem of low sorting efficiency after picking and shelling of Camellia fruits in machinevision, the paper proposes a preference artificial immune network algorithm (aiNet) with multifeatures, which applies the multiobjective optimization of artificial immune network and preference database to extract the multifeatures in color and shape of Camellia objects to input into the immune network for simulation test. The test results show that the multifeatures preference immune network proposed in this paper is feasible. The recognition rate of the network has reached 90%, and the minimum identification time is 60 ms. Compared with the single feature sorting method, this method is more effective, which provides a feasible scheme for the intelligent sorting method of agricultural and forestry targets.

Key words: sorting, machinevision, Camellia fruit, aiNet, multifeatures

摘要: 针对油茶果采摘、脱壳后机器视觉分选效率不高的问题,提出一种多特征偏好人工免疫网络算法,该算法应用人工免疫网络的多目标优化与偏好数据库特征,提取油茶目标的颜色、形态多特征输入免疫网络进行仿真测试。试验结果表明,本文提出的多特征偏好免疫网络的识别率最高达到90%以上。相比单特征分选方法有了较大的提升,证明本文分选方法的有效性,并为农林业目标智能化分选辨识提供一种可行的方案。

关键词: 分选, 机器视觉, 油茶果, 人工免疫网络, 多特征

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