激光生物学报Issue(1)：31-37,7.DOI:10.3969/j.issn.1007-7146.2015.01.005
基于高光谱成像和主成分分析的水稻茎叶分割
The Segmentation of Leaf and Stem of Individual Rice Plant with Hyperspectral Imaging System and Principal Component Analysis
摘要
Abstract
In the study of phenomics,the segmentation of leaf and stem of individual rice plant is very important, which can be used to provide basis for the calculation of phenotypic parameters,such as green leaf area and biomass.Traditional methods are subjective,time-consuming,and labor-intensive.The segmentation with color image,acquired by CCD camera,has shown a poor result.This study introduced an automatic segmentation method of leaf and stem with a hyperspectral imaging system.First,the images of individual rice plant under different wavelength were extracted from original binary stream.Then the principal component analysis (PCA)was used to analyze all the images and extract main principal component images.At last,these main images were used to segment the leaf and stem with digital image processing.The result has shown that this hyperspectral imaging system and method that was used in this study has good segmentation outcome for the leaf and stem of individual rice plant on the tillering stage.This work provides a break-through for high-throughput,non-destructive,and accurate extracting the leaf and stem of rice,and promotes the devel-opment of the plant phenomics.关键词
高光谱成像/图像分割/主成分分析Key words
hyperspectral imaging/image process/principal component analysis分类
化学化工引用本文复制引用
冯慧,熊立仲,陈国兴,杨万能,刘谦..基于高光谱成像和主成分分析的水稻茎叶分割[J].激光生物学报,2015,(1):31-37,7.基金项目
国家高技术研究发展计划（863计划，2013AA102403）；国家自然科学基金资助项目（30921091，31200274）；新世纪优秀人才支持计划 （）
