Objective:

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To build a gray-level matching template by using the gray level information of the microscopic image of the transverse section of Chinese medicinal materials

in order to realize the automatic recognition of the images of Chinese medicinal materials independent of scale and orientation.

Method:

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By using the embedding method of polyethylene glycol (PEG)

the transverse slices of 19 kinds of common rhizomatous medicinal materials were obtained. The images of the slices were taken by digital microscopic imaging technology

and the mosaic grayscale images were obtained by image registration

noise removal and boundary location. The center of the structure of the materials in the images was selected to establish the polar coordinate system

so as to divide grids from the radial and angular directions. By counting the gray information in each grid

the gray information digital matrix that can characterize the microscopic identification characteristics of the materials was obtained. Images in an appropriate sample size was used to train the matrix for generalization of the matrix. The covariance coefficients between the matrix of positive or negative verification sample and the template matrix were calculated to set the best identification parameters. For each medicinal material

80 fan-shaped images were prepared

including 70% of training samples

15% of validation samples and 15% of test samples

and single template and template set were tested with test samples.

Result:

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In the test of 240 images including non-template-set medicinal materials

the correct recognition rate of single-template test was 90.1%

and that of template-set test was 92.5%.

Conclusion:

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This method can well characterize the microscopic identification characteristics of Chinese medicinal materials

with a strong anti-interference ability and less subjective-errors

acquire sample images easily

and provide technical support for the digitization of morphological quality control of Chinese medicinal materials.