Kannan, S. and Vinod, Kumar D and Murali, G. and Baskar., D (2022) Tongue Print Image Recognition and Authentication using Convolutional Neural Networks. In: UNSPECIFIED.
Full text not available from this repository.Abstract
In recent years, tongue print identification has been a hot research topic in biometric applications. The tongue is a critical internal organ that is well-protected from the outside world by the oral cavity. Not only tongue print a cutting-edge biometric technique, but it is also a very effective forensic tool. This article provides a Tongue Print recognition framework for extracting features from tongue images performed using Convolutional Neural Networks Models. The proposed methodology is validated using our own database. Experiment findings demonstrate that the suggested VGG16 attains an F1 Score of 98.9%. According to the results, the suggested biometric identification system is secure, sturdy, and dependable. © 2022 Elsevier B.V., All rights reserved.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Computer Science > Computer Vision and Pattern Recognition |
| Divisions: | Engineering and Technology > Vinayaka Mission's Kirupananda Variyar Engineering College, Salem > Bio-medical Engineering |
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 02 Dec 2025 09:29 |
| URI: | https://vmuir.mosys.org/id/eprint/2938 |
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