利用少量波段近红外光谱图像鉴定玉米种子纯度

为实现玉米杂交种的自动化快速分选,提出了应用少量近红外波段光对玉米种子进行成像,获取种子光谱图像并提取纹理特征来鉴定玉米杂交种纯度的方法。采集5个玉米品种的母本和杂交种在4个短波近红外波段的透射光谱图像和4个中波近红外波段的反射光谱图像,采用白板标定校正光谱图像,运用中值滤波、大津法去除噪声,从背景中分割出种子,应用灰度分布统计,灰度共生矩阵提取纹理特征,对同一粒种子拼接其在各波长处的特征数据,应用主成分分析和正交线性判别分析降维并获得子空间的最佳可分性,使用支持向量机建立透射和反射光谱图像纯度鉴定模型。透射和反射模型对5个玉米品种平均正确鉴别率均在85%以上。表明利用少量波段的近红外光谱图像鉴定玉米杂交种纯度是可行的。

Identification of Maize Seed Purity Based on Spectral Images of A Small Amount of Near Infrared Bands

The method of identifying maize seed purity by analysising seeds spectral images of a small amount of near infrared bands was developed to satisfy the needs of rapid inspection and automatic sorting of maize hybrid seeds.The spectral images of hybrid and female parent of 5 maize varieties at 4 short wave near infrared bands in transmission mode and 4 medium wave near infrared bands in reflection mode were collected.Black-white calibration,median filtering,otsu method were applied to remove the noise and extract the seeds from background.Texture features were extracted by histogram statistics(HS)and gray level co-occurrence Matrix(GLCM).Splicing the feature data at each wavelength,principal component analysis(PCA)and orthogonal linear discriminant analysis(OLDA)were applied to reduce dimensions and obtain the best separability of subspace.The trans-mission and reflection spectral image purity identification model was built by support vector machine (SVM).The average correct identification rate of 5 maize varieties was above 85% both in transmission and reflection models.This research show that it is feasible to use spectral images of a small amount of near infrared bands to identify the purity of maize hybrid seeds.