Research on Spectra Recognition Method for Cabbages and Weeds Based on PCA and SIMCA
ZU Qin1, 2, 3, DENG Wei1, 2*, WANG Xiu1, 2, ZHAO Chun-jiang1, 2
1. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences，Beijing 100097，China 2. National Research Center of Intelligent Equipment for Agriculture，Beijing 100097，China 3. The Electrical Engineering College of Guizhou University，Guiyang 550025，China
Abstract：In order to improve the accuracy and efficiency of weed identification, the difference of spectral reflectance was employed to distinguish between crops and weeds. Firstly, the different combinations of Savitzky-Golay (SG) convolutional derivation and multiplicative scattering correction (MSC) method were applied to preprocess the raw spectral data. Then the clustering analysis of various types of plants was completed by using principal component analysis (PCA) method, and the feature wavelengths which were sensitive for classifying various types of plants were extracted according to the corresponding loading plots of the optimal principal components in PCA results. Finally, setting the feature wavelengths as the input variables, the soft independent modeling of class analogy (SIMCA) classification method was used to identify the various types of plants. The experimental results of classifying cabbages and weeds showed that on the basis of the optimal pretreatment by a synthetic application of MSC and SG convolutional derivation with SG’s parameters set as 1rd order derivation, 3th degree polynomial and 51 smoothing points, 23 feature wavelengths were extracted in accordance with the top three principal components in PCA results. When SIMCA method was used for classification while the previously selected 23 feature wavelengths were set as the input variables, the classification rates of the modeling set and the prediction set were respectively up to 98.6% and 100%.
祖 琴1, 2, 3，邓 巍1, 2*，王 秀1, 2，赵春江1, 2 . 主成分分析和SIMCA的甘蓝与杂草光谱识别方法研究 [J]. 光谱学与光谱分析, 2013, 33(10): 2745-2750.
ZU Qin1, 2, 3, DENG Wei1, 2*, WANG Xiu1, 2, ZHAO Chun-jiang1, 2 . Research on Spectra Recognition Method for Cabbages and Weeds Based on PCA and SIMCA . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(10): 2745-2750.
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