Microscopic Image Segmentation of Chinese Herbal Medicine Based on Region Growing Algorithm

Abstract

In order to effectively separate the target region of the microscopic image of Chinese Herbal Medicine (CHM), and lay the foundation for the subsequent image recognition processing, a microscopic image segmentation method of CHM by using region growing (RG) algorithm is put forward based on the characteristics of the plant microscopic images. Firstly, the CHM microscopic images with different cell structure are regarded as a multi-dimensional matrix to process and established seed label matrix. Secondly, in a given region threshold conditions, the different seed growth points are selected to segmented the different images. Finally, given a fixed growth points, the microscopic images are processed by choosing a different threshold. The experimental results show that CHM image segmentation threshold and seed selection decide the image target extraction. For different CHM images, according to a certain method, the better image segmentation results can be achieved in the case to obtain a suitable threshold value using image information and the seed point adjustment.