量子电子学报, 2019, 36 (2): 151, 网络出版: 2019-04-03   

基于光谱分析的罂粟识别研究

Research of identification of papaver based on spectral analysis
作者单位
1 中国科学院安徽光学精密机械研究所中国科学院大气光学重点实验室, 安徽 合肥 230031
2 中国科学技术大学, 安徽 合肥 230026
摘要
根据排查罂粟的需要,利用光纤光谱仪在室内测量了小麦、罂粟、虞美人和狗尾草等植物在450~1000 nm波长范围内的光谱反射率。运用SPSS统计软件的逐步判别分析方法获得区分四种植物的8个特征波长,以选定的特征波长点建立判别模型进行分析,以罂粟错识率及非罂粟错识率为评价指标,研究了识别效果随特征波长点及特征波长点数目的变化情况。结果表明“红边”附近波长对罂粟及非罂粟的识别有重要影响,利用特征波长组合684.0,706.4,725.2,919.2 nm或684.0,694.3,706.4,725.2 nm 时,罂粟错识率及非罂粟错识率可以降到0%。
Abstract
According to the needs of investigation the illicit cultivation of opium poppy, the spectral reflectance of wheat, opium poppy, corn poppy and green bristlegrass in the wavelength range of 450~1000 nm was measured using a fiber optical spectrometer in the laboratory. Using the stepwise discriminant analysis method of SPSS statistical software, eight characteristic wavelength for distinguishing these four species of plants were obtained. The discriminant model is established with the selected characteristic wavelength point. The discriminant model takes poppy recognition error rate and the non-poppy recognition error rate as evaluation index. The variation of the recognition effect with the number of characteristic wavelength points and characteristic wavelength points was studied. The results showed that the wavelengths near the“red-edge”have an important influence on the identification of poppy and non-poppy. Using two combinations of the four characteristic wavelengths of 684.0, 706.4, 725.2, 919.2 nm or 684.0, 694.3, 706.4, and 725.2 nm, the poppy recognition error rate and non-poppy recognition error rate can be reduced to 0%.

王浩, 秦来安, 靖旭, 何枫, 谭逢富, 侯再红. 基于光谱分析的罂粟识别研究[J]. 量子电子学报, 2019, 36(2): 151. WANG Hao, QIN Lai-an, JING Xu, HE Feng, TAN Feng-fu, HOU Zai-hong. Research of identification of papaver based on spectral analysis[J]. Chinese Journal of Quantum Electronics, 2019, 36(2): 151.

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