摘要
为了对玉米种子进行无损识别分类,对玉米种子的高光谱图像的光谱信息进行分析,探索高光谱图像技术在玉米种子识别分类上的可行性。利用波长范围为400～1 000 nm的高光谱图像采集系统采集11类共528粒玉米样本的高光谱图像;在每个玉米样本上提取感兴趣区域并获取此区域的平均光谱信息,对光谱曲线进行分析,去除12个奇异样本;结合偏最小二乘判别分析法对所选玉米种子样本识别分类。实验结果表明,在所选玉米样本的识别中训练集样本的识别精度可以达到99.22%,测试集样本的识别精度也达到了94.66%。研究结果表明,不同种类的玉米种子的光谱信息具有一定的差异性,利用高光谱图像技术提取其光谱信息对玉米种子品种进行无损识别分类是可行的。
In order to realize nondestructive recognition and classification for maize seed,spectral information of hyperspectral image for maize seed are analyzed.The feasibility of recognition and classification for maize seed is investigated.First,hyperspectral images from 400 nm to 1 000 nm are acquired by hyperspectral image systerm for 528 maize seeds including 11 varities.Then the interested region for each sample is extracted and average spectral information is obtained.Twelve singular samples are removed after spetral curve analysis.Finally,classification model is developed using partial least squares discriminant analysis（PLSDA） for remaining samples.Experimental results indicate that the classification accuracy is 99.22% for the training set and is 94.66% for the testing set.Research results show that nondestructive recognition and classification for maize seed varity is effective using hyperspectral image technology based on the difference of spectral information for different maize seed varities.
出处
《江南大学学报（自然科学版）》
CAS
2012年第2期149-153,共5页
Joural of Jiangnan University (Natural Science Edition)
基金
国家自然科学基金项目(60805014)
江苏省自然科学基金项目(BK2011148)
中央高校基本科研业务费专项基金项目(JUSRP20913
JUSRP21132)
关键词
高光谱图像技术
玉米种类
光谱信息
分类
hyperspectral image technology
maize variety
spectral information
classification
