[Identification of Papaver somni ferum L. and Papaver rhoeas using DSWT-FTIR-RBFNN].
Infrared spectra of Papaver somniferum L. and Papaver rhoeas were obtained directly, quickly and accurately by Fourier transform infrared spectroscopy (FTIR)with OMNI sampler. Discrete stationary wavelet transform was used to extrude local region of infrared spectra of Papaver somniferum L. and Papaver rhoeas. The difference of infrared spectra between Papaver somniferum L. and Papaver rhoeas was extruded. Accurate identification rate is improved greatly. One dimensional discrete stationary wavelet transform was implemented to the infrared spectra of Papaver somniferum L. and Papaver rhoeas. The difference between Papaver somniferum L. and Papaver rhoeas was observed at all scales in wavelet domain. Two scales, at which the difference between Papaver somniferum L and Papaver rhoeas is the most obvious, were selected to extract the features of Papaver somniferum L. and Papaver rhoeas. A feature vector including eight feature parameters was constructed. The feature vector was input to RBFNN for training in order to accurately identify Papaver somniferum L. and Papaver rhoeas. In experiment, the authors used one hundred and twenty-eight couples of data of Papaver somniferum L. and Papaver rhoeas (including seventy-eight couples of training samples and fifty couples of testing samples). The experimental results show that it is effective to apply discrete stationary wavelet transform on the basis of FTIR to identify the Papaver somniferum L. and Papaver rhoeas. The accurate identification rate of Papaver somniferum L and Papaver rhoeas is 99.8% and 99.9% respectively.
Zhang
Chang-jiang
CJ
College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China. zcj74922@zjnu.cn
Cheng
Cun-gui
CG
D001185:Artificial Intelligence; D016571:Neural Networks, Computer; D010207:Papaver / Q000737:chemistry* / Q000145:classification; D017550:Spectroscopy, Fourier Transform Infrared / Q000706:statistics & numerical data*