系统仿真学报 ›› 2018, Vol. 30 ›› Issue (8): 2892-2899.doi: 10.16182/j.issn1004731x.joss.201808010

• 仿真建模理论与方法 • 上一篇    下一篇

水稻叶片颜色可视化模拟方法研究

杨红云1,3, 孙爱珍2,3,*, 杨文姬1,3, 何火娇1,3   

  1. 1. 江西农业大学软件学院,南昌 330045;
    2. 江西农业大学理学院,南昌 330045;
    3. 江西省高等学校农业信息技术重点实验室,南昌 330045
  • 收稿日期:2016-10-21 出版日期:2018-08-10 发布日期:2019-01-08
  • 通讯作者: 孙爱珍(1975-),女,江西新干,硕士,副教授,研究方向为数学建模与应用。
  • 作者简介:杨红云(1975-),男,江西新干,硕士,副教授,研究方向为虚拟农业技术、机器学习。
  • 基金资助:
    国家自然科学基金(61562039,61363041,61462038)

Method of VisualSimulation of Rice Leaf Color

Yang Hongyun1,3, Sun Aizhen2,3,*, Yang Wenji1,3, He Huojiao1,3   

  1. 1. School of Software, Jiangxi Agricultural University, Nanchang 330045, China;
    2. College of Science, Jiangxi Agricultural University, Nanchang 330045, China;
    3. Jiangxi Provincial Key Laboratory of Agricultural Information Technology, Nanchang 330045, China
  • Received:2016-10-21 Online:2018-08-10 Published:2019-01-08

摘要: 提出了一种基于SPAD数据分布图像的水稻叶片颜色渲染方法。通过大田水稻样本试验采集水稻叶片图像并测定叶片SPAD值,分析并构建了SPAD值与叶片图像的R、G、B分量值之间关系模型,模型判定系数分别为0.932 8,0.833 1,0.562 3,表明SPAD与叶片图像R、G颜色分量之间存在相关性。通过SPAD数据分布图像表征SPAD值在叶片表面的空间分布状况,对叶片表面的颜色差异以及随生长时间变化过程进行可视化模拟,并通过微软的Direct3D9.0图形函数库和vc++编程,在前期水稻叶片三维模型的基础上,实现了水稻叶片颜色变化过程的可视化模拟,实现方法具有很好的推广性。

关键词: 水稻, 叶色, SPAD值分布图像, 可视化

Abstract: A color rendering method for rice leaves based on SPAD data distribution image was presented. Rice leaf image was collected and SPAD value was measured by field rice sample test. The relationship model between SPAD values and RGB value of leaf image was analyzed and constructed, and the R2 was 0.932 8, 0.833 1, 0.562 3 respectively. This showed that there was a correlation between SPAD and the red and green color of the leaf image. By the SPAD data distribution image, the spatial distribution of SPAD value on the leaf surface is described. The leaf surface color difference and the change with the growth time were simulated. Through Microsoft's Direct3D9.0 graphics library and vc ++ programming, the visual simulation of rice leaf color change process based on the previous 3D model of rice leaf was achieved. The method has good generalization.

Key words: rice, leaf color, SPAD data distribution image, visualization

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