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An assessment method of tongue image quality in Traditional Chinese Medicine

In the paper, we present a method for evaluating the quality of tongue images in Traditional Chinese Medicine (TCM). First, we preprocess the original images to segment the tongue images. Second, geometric features, texture features and spectral entropy features and spatial entropy features based on Spatial-Spectral Entropy-based Quality (SSEQ) index of tongue images are extracted respectively to form 17 dimensional feature vector for the tongue image quality assessment. Finally, Support vector machine (SVM) model is used to classify the samples. The experimental result shows that our method has a better effect on the tongue image quality assessment for the objectification of tongue diagnosis.