基于图像特征的黄瓜叶片叶绿素含量分布测试方法

A Test Method for Chlorophyll Content Distribution in Cucumber Leaves Based on Image Features

根据叶片叶绿素含量的分布情况,可以直接判断出植物是否缺少营养或者受到环境影响,因此本文以黄瓜叶片作为植物样本,通过深入研究其叶绿素含量的影响因素,探索得到基于图像特征的黄瓜叶片叶绿素含量分布测试方法,首先根据扫描得到的黄瓜叶片高光谱图像,实现其黑白标定及特征提取,利用独立分量法对图像数据完成处理并获得独立分量信号,通过线性回归逐步模型与信号和叶绿素含量的关系式,获取叶片所有像素点相应的叶绿素浓度值,将其与信号进行替换代入后,归一化浓度值并扩展灰度等级范围,采用伪彩色处理后即可直观呈现出黄瓜叶片叶绿素含量的分布情况。经过仿真实验,证明本文的测试方法能够快速、精准地对叶绿素含量的分布情况完成测试,而且具备理想的可行性。

According to the distribution of chlorophyll content in leaves,we can directly determine whether the plants are lack of nutrition or affected by the environment.Therefore,this paper takes cucumber leaves as plant samples,through in-depth study of the influencing factors of chlorophyll content,and explores the method of measuring the distribution of chlorophyll content in Cucumber Leaves Based on image characteristics.First,according to the hyperspectral of cucumber leaves obtained by scanning Image,black-and-white calibration and feature extraction are realized.Independent component method is used to process image data and obtain independent component signal.Through linear regression step-by-step model and the relationship between signal and chlorophyll content,the corresponding chlorophyll concentration value of all pixels in the leaf is obtained.After replacing it with the signal,the concentration value is normalized and the gray level range is expanded After pseudo color treatment,the distribution of chlorophyll content in cucumber leaves can be visualized.Through the simulation experiment,it is proved that this method can test the distribution of chlorophyll content quickly and accurately,and it has ideal feasibility.