Natural tongue physique identification using hybrid deep learning methods

Traditional Chinese Medicine (TCM) illustrates that the physique determines the susceptibility of human to certain diseases and treatment programs for illness. Tongue diagnosis is an important way to identify the physique, but now it is performed by the doctor's professional experience and the design of a questionnaire. Consequently, accurate physique identification cannot be obtained easily. In this paper, we propose a new method to identify the physique through wild tongue images using hybrid deep learning methods. It begins with constructing a large number of tongue images that are taken in natural conditions, instead of in a controlled environment. Based on the resulting database, a new method of tongue coating detection is put forward that applies a rapid deep learning method to complete the initial tongue coating detection, and then utilizes another deep learning method, a calibration neural network, to further improve the accuracy of tongue detection. Finally, an effective deep learning method is applied to identify the tongue physique. Experiments validate the proposed method, illustrating that physique identification can be performed well using hybrid deep learning methods.