Image identification for microscopic structures of Mongolian herbal flowers with invariant moments.
- Author:
Surong HASI
1
;
Guleng AMU
;
Luyan GAO
;
Shisan QI
Author Information
1. College of Veterinary Medicine, Inner Mongolia Agriculture University, Huhhot 010018, China.
- Publication Type:Journal Article
- MeSH:
China;
Flowers;
ultrastructure;
Image Processing, Computer-Assisted;
methods;
Pattern Recognition, Automated;
methods;
Plants, Medicinal;
ultrastructure
- From:
Journal of Biomedical Engineering
2008;25(1):146-149
- CountryChina
- Language:Chinese
-
Abstract:
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.
