Microscopic characteristics of several Mongolian Herbal flowers were extracted by improved Pseudo-Jacobi (p = 4, q = 2)-Fourier Moments (PJFM's), and 368 different versions of 28 microscopic characteristics of these herbs were identified by using the minimum-mean-distance rule. The experimental results showed that the average identification rate reaches as high as 98.1%. Therefore, this study can provide new techniques for digitalization and visualization of microscopic characteristics of Mongolian Herbs.
China ; Flowers ; ultrastructure ; Image Processing, Computer-Assisted ; methods ; Pattern Recognition, Automated ; methods ; Plants, Medicinal ; ultrastructure