OBJECTIVE： To extract the feature of Achyranthes bidentata and Cyathula officinalis， and to establish image recognition 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 data matrix， and then data matrix was standardized by Zscore function； principal components were analyzed through Princomp function. 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 analysis， 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.