ABSTRACT
This study was aimed to investigate the impact of rotation sampling on feature parameters of texture im-ages of Chinese herbal medicine. Four Chinese herb medicine with various shape and texture feature were taken as research materials. Images of complete and incomplete herbal medicine were collected respectively after different ro-tation angles. The 26 parameters were extracted by gray-level co-occurrence matrix and grayscale gradient matrix. The impact of rotation sampling on feature parameters was investigated through analysis of variation tendency and range of 26 parameters. The results showed that if the Chinese herbal medicine was complete, the 26 parameters were not impacted by the rotation angle, whereas the 26 parameters were impacted by the rotation angle and the im-pact will be more obvious when the shape of Chinese herb medicine was irregular. It was concluded that in order to get a high quality of images and construct a well identification model based on the parameter of texture features, we must consider the impact of rotation angle on the parameters to Chinese herbal medicine with various shapes and tex-ture features.
ABSTRACT
This study was aimed to explore the impact of integrality of Chinese herbal medicine on parameters of tex-ture feature in transverse section images. Three Chinese herbal medicine of Semen Arecae, Radix et Rhizoma Rhei and Radix A tractylodis Macrocephalae with different texture features were taken as research materials. Parts of Chi-nese herbal medicine were cut off from the whole by equal proportions. The 26 parameters were extracted by gray-level co-occurrence matrix and grayscale gradient matrix. The similarities and differences of 26 parameters of texture feature in the parts and whole, rectangular and fan-shaped Chinese herbal medicine were compared. The results showed that parameters of Semen A recae and Radix et Rhizoma Rhei with radial or annular texture had better con-sistency in whole and fan-shaped parts. Parameters of Radix A tractylodis Macrocephalae with irregular texture fea-ture were approximately the same in the whole and rectangular parts. It was concluded that whether parameters of texture features in parts Chinese herbal medicine can present the whole were related to its texture feature and the shape of the parts. This study provided the basis for collection of Chinese herbal medicine when sampling images. It also laid a foundation for the extraction of accurate parameter of texture feature.
ABSTRACT
This study was aimed to compare the difference of parameters of texture feature in the transverse section images of the same and different Chinese herbal medicine. A total of 26 parameters of herbal medicines were ex-tracted by gray-level co-occurrence matrix and grayscale gradient matrix. The graph of mutative curve was drawn. And differences of 26 parameters of texture feature in the same and different Chinese herbal medicine were com-pared. The results showed that parameters of texture feature extracted by gray-level co-occurrence matrix and grayscale gradient matrix had similarities and differences in the same and different Chinese herbal medicine. It was concluded that the method can show the texture feature scientifically and quantitatively. It also laid a foundation for the establishment of an automatic identification model, but the parameters still had instability. All these remind us to find some parameters which can show the details of texture feature preferably, thus perfect the extracted method of texture features in Chinese herbal medicine.
ABSTRACT
This study was aimed to establish the classification method of Chinese herbal medicine based on feature parameters extracted from images of herbal transverse section, in order to explore the feasibility of automatic identi-fication method of herbal medicine. The extracted 26 parameters of 18 herbal medicine images by gray-level co-oc-currence matrix and grayscale gradient matrix were used as the basic data set. And the minimum covariance determi-nant (MCD) was used to delete the outliers. A total of 18 identification models were established using the native Bayes method and BP neural network methods. The results showed that the average correct rates of models were 90%. It was concluded the feasibility of using these models in the establishment of the automatic identification method of herbal medicines. It provided new technologies for the quantitative, scientific and objective identification of Chinese herbal medicine.