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中国农学通报

中国农学通报 ›› 2013, Vol. 29 ›› Issue (31): 96-100.doi: 10.11924/j.issn.1000-6850.2013-0534

所属专题： 园艺

• 林学 园艺 园林 • 上一篇    下一篇

基于数字图像的番茄黄化曲叶病毒病色彩分析研究

李俊1,陈振德2   

  • 收稿日期:2013-02-28 修回日期:2013-03-10 出版日期:2013-11-05 发布日期:2013-11-05
  • 基金资助:
    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)

Study on the Color Analysis of Tomato Yellow Leaf Curl Virus Disease Based on Digital Images

Li Jun1, Chen Zhende2   

  • Received:2013-02-28 Revised:2013-03-10 Online:2013-11-05 Published:2013-11-05

PDF (PC)

539

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

Abstract: In order to achieve rapid non-destructive monitoring of tomato yellow leaf curl virus disease, we analyzed the images of tomato leaves using computer image processing technology. We compared 9 color parameters in 3 color systems. The study showed that there were significant differences in five color parameters. In a further study on distribution statistics, we found the optimal distinguish interval of each parameter. Each distinguish rate of G, Y and Cb is more than 70%. The optimal distinguish interval of each 3 value is 135, 121 and 110. This provided important parameter basis for the follow-up study on identify model. The result shows that it’s feasible to identify tomato yellow leaf curl virus disease based on color analysis.

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