Objective:

2

To construct the color matching template irrelevant to size and rotation according to the types and distribution characteristics of colors in images of Chinese herbal pieces

in order to establish color characterization and image identification methods for Chinese herbal pieces.

Method:

2

Totally 20 types of Chinese herbal pieces were selected

including rhizomes

flowers

seeds and fruits.For each sample

two observation surfaces were selected to extract color parameters in foreground through image processing such as image segmentation

model transformation from RGB to

L

*

a

*

b

*

.Color vectors of the two observation surfaces were sequenced in a descending order

scaled to a certain size by interpolating

and combined into an integrated color vector in a weight ratio of 1∶1.As for centripetally distributed observation surface images(e.g.transverse section)

corrosion operation was conducted to extract the color components of each ring from outer to inner by circles

which were then ordered and scaled.The integrated color vector was used as initial template for training

the correlation coefficient between each sample and the template was calculated

and the interval estimation of positive samples were carried out by

t

test.With the total recognition rate as an indicator

the optimal template dimensions

width of ring and training volume were ultimately determined.

Result:

2

The visualization results of the trained templates of the varied herbal pieces were easy to be visually distinguished.After 260 samples of the herbal pieces were tested

the template of a and b components was better than that of

L

*

a

*

and

b

*

in terms of recognition performance

with

a

*

recognition accuracy of 95.8%(249/200).

Conclusion:

2

Color characteristics of images from two observation surfaces of Chinese herbal pieces are integrated to obtain the combined color feature vector

so as to achieve preferable recognition results for samples from both the same and different medicinal parts.This method boasts a strong anti-interference ability of random variation of sample shape

sampling part and color.