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基于数字图像的番茄黄化曲叶病毒病色彩分析研究
引用本文:李俊,陈振德.基于数字图像的番茄黄化曲叶病毒病色彩分析研究[J].中国农学通报,2013,29(31):96-100.
作者姓名:李俊  陈振德
作者单位:1青岛科技大学生态环境与农业信息化研究所,山东青岛266042; 2青岛农业科学研究院,山东青岛266100
基金项目:青岛市科技支撑计划“番茄黄化曲叶病毒病综合防控技术研究”(11-2-3-31-nsh)
摘    要:为实现番茄黄化曲叶病毒病的快速无损监测,利用计算机图像处理技术对番茄叶片图像进行研究。在3种颜色系统中比较9种颜色参数,发现其中5种色彩参数存在显著差异,通过进一步的分布统计研究,发现了各参数的最优区分区间。其中G、Y、Cb 3个值对感病叶片的区分率均达到70%以上,最优区分点分别在135、121和110,可以作为TYLCVD的特征参数应用于识别模型为后续研究识别模型提供重要的参数依据。试验结果表明,基于色彩分析法对番茄黄化曲叶病毒病进行识别是可行的。

关 键 词:产气性能  产气性能  
收稿时间:2013/2/28 0:00:00
修稿时间:2013/3/10 0:00:00

Study on the Color Analysis of Tomato Yellow Leaf Curl Virus Disease Based on Digital Images
Li Jun,Chen Zhende.Study on the Color Analysis of Tomato Yellow Leaf Curl Virus Disease Based on Digital Images[J].Chinese Agricultural Science Bulletin,2013,29(31):96-100.
Authors:Li Jun  Chen Zhende
Institution:1Qingdao University of Science and Technology Institute of Eco-environment & Agriculture Information, Qingdao Shandong 266042; 2Qingdao Academy of Agricultural Sciences, Qingdao Shandong 266100
Abstract:In order to achieve rapid non-destructive monitoring of tomato yellow leaf curl virus disease, the author analyzed the images of tomato leaves using computer image processing technology. The author compared 9 color parameters in 3 color systems. The study showed that there were significant differences in 5 color parameters. In a further study on distribution statistics, it was found the optimal distinguish interval of each parameter. Each distinguish rate of G, Yand Cb was more than 70%. The optimal distinguish interval of each 3 value was 135, 121 and 110. This provided important parameter basis for the follow-up study on identify model. The result showed that it' s feasible to identify tomato yellow leaf curl virus disease based on color analysis.
Keywords:tomato yellow leaf curl virus  computer vision  image processing  RGB  HIS  YCbCr  characteristic  value extraction
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