基于计算机视觉技术的烟叶成熟度判定方法

Determination of tobacco leaf maturity degree based on computer vision technology

快速定量检测烟叶成熟度可为烟叶成熟收割提供决策依据。通过对烟叶样品图像数据进行处理与变换,得到烟叶图像的HSV颜色值,使用线性回归分析法建立烟叶图像HSV颜色值与叶绿素含量之间的函数关系,以及烟叶叶绿素含量与SPAD值之间的函数关系;利用烟叶成熟度与SPAD值之间的函数关系,构建烟叶图像HSV颜色特征值与烟叶成熟度之间的关系模型TMDHSV,从而建立起基于计算机视觉技术的烟叶成熟度判定方法。试验结果表明,该方法具有较好的可行性,可为快速定量检测烟叶成熟度提供技术支撑。

Fast quantitative testing on the maturity of tobacco leaves is valuable to the tobacco harvest. The HSV color value of tobacco leaves was acquired approach via the process and exchange of image data collected from the sample leaves. The functional relationship between HSV color value and chlorophyll content and between chlorophyll content and SPAD value were established by the linear regression analysis. Based on the functional relationship between maturity degree and SPAD value, the TMDHSV relation model was set up between HSV color value and leaf maturity. And then the method was established for determination of tobacco leaf maturity degree based on computer vision technology. The approach has been proved feasible to acquire the maturity values of the growing tobacco leaves quickly.