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The traditional Chinese medicine (TCM) tongue diagnosis is a kind of examination method to observe the physiological characteristics and pathological changes of the body, and provides a basis for the syndrome differentiation and treatment of the disease. The color of tongue proper and tongue coating can reflect the health of the human body. Although a significant amount of work has been focused on using digital images and tongue color classification, spectral-based methods need to be developed to effectively evaluate the grading of color of the tongue. In this paper, a spectral range of 400–1000 nm visible hyperspectral image system was used to collect the hyperspectral tongue images, and a two-layer deep brief network (DBN) model was proposed to classify the color grading of red tongue proper and yellow tongue coating in TCM. The DBN was applied on the spectral curve and spatial region separately to obtain the spectral and spatial feature in the first layer. And then the second layer was implemented as a classifier based on the DBN. Compared with the comparison experiments, the experimental results show the effectiveness of the spectral-spatial with the two-layer DBN model when classify the color grading of red tongue proper and yellow tongue coating. And with the average precision and recall were 0.7503 and 0.7651 for color grade of red tongue proper, 0.8029 and 0.8151 for color grade of yellow tongue coating, the proposed method can provide a new technique for the objective and digitizing development of tongue diagnose in TCM.
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