Attribute based Double Bounded Rough Neutrosophic Sets in Facial Expression Detection

Authors

  • Praba B Department of Mathematics
  • Pooja S Department of Electronics and Communication
  • Nethraa Sivakumar Department of Electronics and Communication

Keywords:

Double Bounded Rough Neutrosophic Sets, Facial Expression Detection, Facial key points, Neutrosophic sets, Fuzzy set, Rough Set

Abstract

In this paper, a hybrid intelligent structure called “Double Bounded Rough Neutrosophic Sets†is defined, which is a combination of Neutrosophic sets theory and Rough sets theory. Further, the Attribute based Double Bounded Rough Neutrosophic Sets was implemented using this hybrid intelligent structure for Facial Expression Detection on real time data. Facial expression detection is becoming increasingly important to understand one’s emotion automatically and efficiently and is rich in applications. This paper implements some of these applications of facial expression such as: differentiating between Genuine and Fake smiles, prediction of Depression, determining the Degree of Closeness to a particular Attribute/Expression and detection of fake expression during an examination. With the onset of COVID – 19 pandemic, majority of people are choosing to wear masks. A suitable method to detect Facial Expression with and without mask is also implemented. Double Bounded Rough Neutrosophic Sets proposed in this paper is found to yield better results as compared to that of
individual structures (Neutrosophic sets theory or Rough sets theory)

Downloads

Download data is not yet available.

Downloads

Published

2022-04-01

Issue

Section

SI#1,2024: Neutrosophical Advancements And Their Impact on Research

How to Cite

B, P. ., S, P. ., & Sivakumar, N. . (2022). Attribute based Double Bounded Rough Neutrosophic Sets in Facial Expression Detection. Neutrosophic Sets and Systems, 49, 324-340. https://fs.unm.edu/nss8/index.php/111/article/view/2488