Tongue Image Texture Classification Based on Xception

Abstract

Tongue image texture analysis is the main content of inspection diagnostics in traditional Chinese medicine (TCM). The tough and tender classification for tongue image is mainly represented by image texture. The traditional extraction method of texture feature is not robust and is not suitable for variable illumination and different image acquisition equipment. So we select 'Xception' as the main network model to complete feature extraction firstly. Then, two full connection layers and a softmax layer are combined, two dropout layers are added in their middle to form a classification network. The experimental results show that the better accuracy rate can be obtained by our method.