Title
Automatic Tongue Verification Based on Appearance Manifold Learning in Image Sequences for the Internet of Medical Things Platform.
Abstract
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.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2859913
IEEE ACCESS
Keywords
Field
DocType
Human tongue,biometrics,appearance manifold learning,image sequence,LPP and IoMT
Computer vision,Embedding,Computer science,Robustness (computer science),Exploit,Artificial intelligence,Biometrics,Nonlinear dimensionality reduction,Tongue,Manifold,Distributed computing,The Internet
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
Yang Xin1297.03
Yankun Cao234.74
Zhi Liu32314.28
Yuling Chen42710.33
Li-zhen Cui528271.41
Yaowen Zhu600.68
Haixia Hou7131.64
Guangzhe Zhao854.11
Mingyu Wang913524.90