Automatic Tongue Verification Based on Appearance Manifold Learning in Image Sequences for the Internet of Medical Things Platform

The tongue is the only human organ that can stick out of the body. Using the human tongue is considered to be a novel biometrics method because of its rich individual characteristics. How to represent the dynamic shape changes of the tongue is a challenge for identity verification. A new framework for human tongue modeling and recognition based on image sequences is proposed in this paper. In this framework, we exploit appearance manifold learning to obtain a low-dimensional embedding of the sequence of tongue images, and we propose nearest manifold measurement for measuring the similarities in multiple manifolds. Based on the database of tongue image sequences, the results of our experiments showed that the proposed framework not only can effectively perform tongue biometric recognition but can also provide robustness, which is very important for the Internet of medical things platform.

Abstract licence: CC BY-NC-ND

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