| 基于计算机视觉技术的番茄叶片叶绿素含量的检测 |
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| 引用本文： | 柴阿丽,李宝聚,王倩,石延霞,黄海洋.基于计算机视觉技术的番茄叶片叶绿素含量的检测[J].园艺学报,2009,36(1):45-52. |
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| 作者姓名： | 柴阿丽 李宝聚 王倩 石延霞 黄海洋 |
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| 作者单位： | （中国农业科学院蔬菜花卉研究所，北京100081；北京师范大学数学科学学院，北京100875） |
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| 基金项目： | 国家高技术研究发展计划(863计划)，国家自然科学基金，国家科技部科研院所社会公益研究专项基金，农业部园艺作物遗传与改良重点开放实验室项目，国家基础科学人才培养基金，国家自然科学基金 |
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| 摘 要： | 研究利用计算机视觉技术快速测定叶绿素含量的方法，建立了根据番茄叶片颜色特征确定其叶绿素含量的一元二次拟合模型。在计算机视觉图像采集系统中采集番茄叶片图像，利用MATLAB图像处理工具提取图像的颜色特征参数，对颜色特征参数和番茄功能叶叶绿素含量做相关分析，建立回归模型。结果表明：RGB颜色系统的R/G、(G-R)/(G+R)、G-R、色度坐标r、r-g及HIS颜色系统的H值均与叶绿素含量呈极显著非线性相关性，可用于测定番茄叶片叶绿素含量。从建立的6组模型中筛选出拟合度较高的3组模型进行检验，预测误差在0～22.22%之间。用预测精度最高的G-R颜色特征预测叶绿素含量的模型为Chl.a = 0.0926 + 0.1208 (G-R) - 0.0009 (G-R)2，Chl b = - 0.0252 + 0.0397 (G-R) - 0.0003 (G-R)2和Chl.(a+b) = 0.1271 + 0.1600 (G-R) - 0.0011 (G-R)2。
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| 关 键 词： | 计算机视觉 叶绿素含量 番茄叶片 颜色特征 |
| 收稿时间： | 2008-06-11 |
Detecting Chlorophyll Content of Tomato Leaves with Technology of Computer Vision |
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| CHAI A-li,LI Bao-ju,WANG Qian,SHI Yan-xia,HUANG Hai-yang.Detecting Chlorophyll Content of Tomato Leaves with Technology of Computer Vision[J].Acta Horticulturae Sinica,2009,36(1):45-52. |
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| Authors: | CHAI A-li LI Bao-ju WANG Qian SHI Yan-xia HUANG Hai-yang |
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| Institution: | (Institute of Vegetables and Flowers，Chinese Academy of Agriculture Sciences，Beijing 100081，China；Department of Mathematics Beijing Normal University，Beijing 100875，China) |
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| Abstract: | The rapid methods detecting chlorophyll concentration by the computer vision technology，and a unary quadratic model to predict chlorophyll content based on color parameters of tomato leaf images have been established in this study．The images of tomato leaves were taken in the image acquisition system，then the color characteristics were extracted with the MATLAB image processing software．The correlation between color parameters of tomato digital image and chlorophyll content of tomato functional leaf were analyzed by nonlinear regress models．The results showed that the color characteristics such as R/G、(G-R)/(G+R)、G-R、r、r-g in the RGB color system，and H-value in the HIS color system were significantly correlation with chlorophyll content of tomato leaf at . 6 sets of prediction model were established and among them 3 models with high fitting degree were selected to use．The prediction accuracy of the selected model were tested，and error ranged 0 to 22.22%．According to the determination coefficients and RMSE (root mean square error)，G-R was the best color characteristic to predict chlorophyll content of tomato leaf. The corresponding models are Chl a = 0.0926 + 0.1208 (G-R) - 0.0009 (G-R)2，Chl b = - 0.0252 + 0.0397 (G-R) - 0.0003 (G-R)2 and Chl a+b = 0.1271 + 0.1600 (G-R) - 0.0011 (G-R)2. |
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| Keywords: | tomato Machine vision chlorophyll content tomato leaf color characteristic |
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