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利用图像识别技术计算薇甘菊锈病的相对病斑面积
引用本文:任行海,刘博,乔曦,王福宽,钱万强,万方浩,刘怀.利用图像识别技术计算薇甘菊锈病的相对病斑面积[J].生物安全学报,2021,30(1):72-77.
作者姓名:任行海  刘博  乔曦  王福宽  钱万强  万方浩  刘怀
作者单位:西南大学植物保护学院, 重庆 400715;中国农业科学院基因组研究所, 广东 深圳 518120;广西大学机械工程学院, 广西 南宁 530003
基金项目:深圳市大鹏新区科技创新和产业发展专项资金项目(KJYF202001-03);深圳市孔雀团队项目(KQTD20180411143628272);深圳市大鹏新区科技创新和产业发展专项资金资助项目(PT202001-06);国家自然科学基金青年科学基金项目(31801804)
摘    要:目的]为了定量评估薇甘菊柄锈菌对薇甘菊的防控效果,研发一种基于图像识别技术的高效、准确的薇甘菊叶片相对病斑面积的计算方法.方法]利用图像识别、网格法、复印称重法3种相对面积的计算方法,分别计算薇甘菊感染柄锈菌后的相对病斑面积,并结合以手动分割的结果作为标准,计算各方法的绝对准确率和绝对误差并作为评价指标,最终对3种...

关 键 词:薇甘菊锈病  相对病斑面积  图像分割  ExG+ExR算法
收稿时间:2020/9/18 0:00:00
修稿时间:2020/11/26 0:00:00

Calculation of spot area of Mikania micrantha rust based on image processing technology
REN Xinghai,LIU Bo,QIAO Xi,WANG Fukuan,QIAN Wanqiang,WAN Fanghao,LIU Huai.Calculation of spot area of Mikania micrantha rust based on image processing technology[J].Journal of Biosafety,2021,30(1):72-77.
Authors:REN Xinghai  LIU Bo  QIAO Xi  WANG Fukuan  QIAN Wanqiang  WAN Fanghao  LIU Huai
Institution:College of Plant Protection, Southwest University, Chongqing 400715, China;Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong 518120, China;School of Mechanical Engineering, Guangxi University, Nanning, Guangxi 530003, China
Abstract:Aim] To quantitatively evaluate the biological control effect of rust (Puccinia spegazzinii) in Mikania micrantha, an efficiently and accurate image processing technology was developed for calculating the relative lesion area (RLA) of M. micrantha leaf.Method] In this study, we calculated the RLA of infected leaf in M. micrantha based on three methods, including image processing technology, grid method and photocopy weighing method, respectively. In addition, using the manual segmentation method to calculate the RLA as the standard, the absolute accuracy and absolute error of above three methods were calculated and used as the systematic and scientific evaluation index.Result] The result shows that compared with grid method and copy method, the image processing technology based on Excess Green+Excess Red (ExG+ExR) algorithm segmentation disease spot can quickly and accurately calculate the RLA of infected leaf in M. micrantha with 98% absolute accuracy and 1.81% absolute error rate. In addition, it only takes 45.77s to process a 4608×3456 pixels color image.Conclusion] Compared with the traditional method, because the image processing technology could accurately and quickly segment the lesion area and the healthy area, the accurate RLA of infected leaf could be obtained.
Keywords:Mikania micrantha rust  RLA  image segmentation  ExG+ExR clustering
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