Feature Extraction and Image Recognition of Achyranthes bidentata and Cyathula officinalis / 中国药房

ABSTRACT

OBJECTIVE:To extract the feature of Achyranthes bidentata and Cyathula officinalis,and to establish image recog-nition method. METHODS:The microscopic image stitching of A. bidentata and C. officinalis was implemented by MATLAB. The color,invariant moment,stripes and the features of vascular bundle in cross section were extracted. The data was organized into da-ta matrix,and then data matrix was standardized by Zscore function;principal components were analyzed through Princomp func-tion. BP nerve network recognition mode was adopted. RESULTS:The microstructures in the micro images of the samples were kept integrated. The measured data of 27 characteristics were acquired in each group of sample. Through principal component analy-sis,the parameters of 11 main components were selected to establish BP never network. The average recognition rate of BP nerve network was 100% between 2 medicinal material relatives (n=50). CONCLUSIONS:The method can be used for micro-image auto Stitching of Chinese medicinal materials and image recognition of A. bidentata and C. officinalis.