[Study of feature extraction methods for maize's near infrared spectra in biomimetic pattern recognition].
Near infrared spectrum is an important step in near infrared spectrum qualitative analysis, which influences the qualitative analysis results directly. Diffuse transmittance measurements mode was used to collect spectral data of eight maize varieties. PCA, ICA, PLS-DA and wavelet transformation were used to extract features of pretreated data. Finally, we used the test set data to test the recognition models of eight maize varieties which were built based on biomimetic pattern recognition (BPR). We draw a conclusion that PLS-DA can make models get higher average correct recognition rate than PCA, ICA and Wavelet transformation.
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China. lfshen@cau.edu.cn
Li-feng
LF
Shen
Shi-qiang
SQ
Jia
Ting-ting
TT
Guo
Wen-jin
WJ
Wu
Yan-lu
YL
Yan
Dong
D
An
D032701:Biomimetics; D010363:Pattern Recognition, Automated; D019265:Spectroscopy, Near-Infrared; D058067:Wavelet Analysis; D003313:Zea mays