基于高光谱的砀山酥梨炭疽病害等级分类研究

Research on Anthrax Disease Classification of Dangshan Pear Based on Hyperspectral Imaging Technology

为了检测病害的不同程度等级,以接种炭疽病的砀山酥梨为研究对象,利用高光谱成像技术对病害进行建模分类。在400~1000nm光谱区域采集砀山酥梨样本接种炭疽病初期到发病、直至腐烂整个过程的时序高光谱图像;采用阈值分割法对图像进行背景分割,并基于有效的光谱区域做主成分分析,选取第二主成分(PC2)提取染病的感兴趣区域,并对感兴趣区域用权重系数法作特征值提取;采用非监督的分类算法对特征值进行聚类分析。通过对210个样本集进行观察分析发现,样本分类的有效程度为98.41%。实验结果表明,采用高光谱成像无损检测技术对砀山酥梨炭疽病不同程度的分类是有效的。

To detect the disease of different levels,this article took Dangshan pear which gets vaccinated of anthrax as the research object,using hyperspectral imaging technology for the modeling of disease classification.In 400~1000nm spectral region,we collected the sequential hyperspectral images of the whole process of Dangshan pear samples from inoculation of anthrax to morbidity and to decompose,used threshold segmentation to conduct background segmentation of images,and did principal composition analysis based on the effective spectral region.We selected the second principal component(PC2)to extract the infected region of interest,and used weight coefficient method for eigenvalue extraction of region-of-interest and used unsupervised classification algorithm for clustering analysis of characteristic value.Through observation and analyzation of 210 sample sets,it comes that the effective sample classification is 98.41%.The experimental results show that it is valid to make use of hyperspectral imaging nondestructive testing technology for the classification of the anthrax disease of Dangshan pear of different levels.