节点文献

田间害虫图像识别中的特征提取与分类器设计研究

Feature Extraction and Classification in the Image Recognition for Agricultural Pests

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 张红涛胡玉霞赵明茜邱道尹张孝远张恒源

【Author】 ZHANG Hong-tao1,HU Yu-xia2,ZHAO Ming-qian3,QIU Dao-yin1,ZHANG Xiao-yuan4,ZHANG Heng-yuan1(1.Institute of Electric Power,North China Institute of Water Conservancy and Hydroelectric Power,Zhengzhou 450011,China;2.College of Electric Engineering,Zhengzhou University,Zhengzhou 450001,China;3.Center of Management and Service for the Eexperiment and Demonstrate Base on Morden Agricultural Sciences and Technique,Henan Academy of Agricultural Sciences,Zhengzhou 450002,China;4.Department of Information Engineering,Henan Vocational & Technical College,Zhengzhou 450046,China)

【机构】 华北水利水电学院电力学院郑州大学电气工程学院河南省农业科学院现代农业科技试验示范基地管理与服务中心河南职业技术学院信息工程系

【摘要】 特征提取和分类器的设计是田间害虫图像识别中的关键环节。针对害虫目标的二值化图像提取出面积、周长、复杂度等7个形态学特征,并进行归一化处理;建立了9种害虫的模板库及隶属度函数,并基于最小最大的原则进行模糊决策分析;对稻纵卷叶螟、棉铃虫等田间危害严重的9种害虫进行识别分类的识别率达86%以上。

【Abstract】 The feature extraction and the classification design are the key parts in the image reco-gnition for agricultural pests.Seven morphological features from the binary images of agricultural field pests,such as area,perimeter,and so on were extracted and normalized.The data templates of nine pieces of pests and the subject function were set and the fuzzy decision is analyzed based on the fuzzy minimums and maximums rule.The result shows that the fuzzy classification can be nine pieces of pests that harmed seriously,such as rice leaf folder,cotton bollworm,etc.The correct recognition accuracy is over 86%.

【基金】 河南省自然科学基金资助(2008B510014);华北水利水电学院青年基金资助(HSQJ2008006)
  • 【文献出处】 河南农业科学 ,Journal of Henan Agricultural Sciences , 编辑部邮箱 ,2008年09期
  • 【分类号】TP391.41
  • 【被引频次】33
  • 【下载频次】559
节点文献中: 

本文链接的文献网络图示:

本文的引文网络