Abstract: The horizontal attenuated total reflectance Fourier transform infrared spectroscopy (HATR-FTIR) was applied to classification of 3 ptychomitrium, including ptychomitrium dentatum (Mitt.) Jaeg., Ptychomitrium polyphylloides (C. Muell.) Par and Ptychomitrium sinense (Mitt.) Jaeg. The technique of discrete wavelet transform was used to extract the features of the similar FTIR of the 3 Ptychomitrium. Through analyzing and comparing the characteristic vector extraction in 3, 4 detail decomposition layers and training the feature variables via radial basis function neural network (RBF-NN), the characteristic extraction vectors of the FTIR of the 3 Ptychomitrium were classified by the network which training out by RBF-NN. By means of the verification of 120 different samples, it was shown that the feasibility of establishing the models with FTIR-DWT-RBF-NN method to identify among Ptychomitrium dentatum (Mitt.) Jaeg., Ptychomitrium polyphylloides (C. Muell.) Par. and Ptychomitrium sinense (Mitt.) Jaeg.