高光谱成像技术和主成分分析识别玉米籽粒的胚

摘要：为了分割玉米籽粒的胚部分，本研究搭建了一套高光谱成像系统用于获取波段范围为500～900 nm的高光谱反射图像。主成分分析（PCA）方法对样本高光谱数据进行降维以便选择少量有效波长构建多光谱成像系统。研究发现，采用可见光（VIS）区域的3个有效波长510、555和575 nm获得的主成分（PC）图像获得了较好的识别结果。100个独立样本用于评估算法性能，结果表明，样本中97.0%的胚可以从玉米籽粒中正确分离。

Identification of maize kernel embryo based on hyperspectral imaging technology and PCA

To segment the embryo from the maize kernel, a hyperspectral imaging system has been built for acquiring reflectance images from maize kernels in the spectral region between 500 and 950 nm. Hyperspectral images of maize samples were evaluated using principal components analysis (PCA) with the goal of selecting several effective wavelengths that could potentially be used in a multispectral imaging system. The second principal component images using three effective wavelengths 510, 555 and 575 nm in the visible spectral (VIS) had good identification results under investigation. For the investigated independent test samples, 97.0% of embryos on samples were correctly separated from the maize kernels.