Image Analysis For The Microscopic Characteristics Of Mongolian Herbal Flowers With Invariant Moments

Traditional Mongolian medicine is one of most important parts in Mongolian cultural heritages, and also is one of bright spots in eastern traditional medicinal treasury.[0] Mongolian Herbs are utilized more and more in the modern medicine today. However, the precise and impersonal identification methods was imperative for powdered Mongolian Herbs,because of the variations caused by different production spots, different harvest seasons, different storing and processing methods of Herbs, and coming forth of some fake medicines. Almost all of preparations of Mongolian traditional medicines were made of several to dozens of powdered Herbs, therefore, it is difficult to identify the exact components of the preparations according to their appearances. For developing and improving the identification and certification methods of traditional Mongolian medicine, commonly used Mongolian Herbal Flowers, were emulated and identified by using Pseudo-Jacobi(p=4,q=3)-Fourier Moments(PJFM's), image processing and pattern recognition in this paper on the basis of skillfully combination of advanced computer techniques and traditional microscopic identification methods according to the distinct microscopic characteristics of the Herbal flowers and their specificity and stability of the tissue structures.Original image database of 14 species of Mongolian Herbal Flowers were established using their main microscopic characteristics, and these microscopic characteristic images were digitalized and reconstructed in our study. The experimental result indicated that the main information of original images could be recovered by finite number of PJFM's, and the values of invariant moments of microscopic characteristics were much different among different microscopic images from different Mongolian Herbal flowers. Therefore, PJFM's can be used to describe different microscopic characteristics of Mongolian Herbal flowers. The training sample set was established by using 130 different versions of pollen granules which came from 13 species of Mongolian Herbal Flowers, and the average recognition rate was reached 98.2%. Then, 1216 different versions of 76 microscopic characteristics of 14 species of Mongolian Herbal Flowers were identified, and the average recognition rate was reached 98.45%. Therefore, PJFM's can be used for feature selection and extraction of microstructure characteristics in microscopic identification of Mongolian Herbal Flowers, and may pave the way for accomplishing automatic check and microscopic identification. This study results can supply a gap for the digitalization and visualization of Mongolian Herbs, and establish an important foundation for globalization of Mongolian Herbs.