Open AccessImproved Approach for Identification of Real and Fake Smile using Chaos Theory and Principal Component Analysis
Author(s) -
Hayder Ansaf,
Hayder Najm,
Jasim Mohammed Atiyah,
Oday A. Hassen
Publication year - 2019
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.54.5.20
Subject(s) - principal component analysis , computer science , face (sociological concept) , artificial intelligence , identification (biology) , component (thermodynamics) , implementation , chaos (operating system) , chaos theory , analytics , facial recognition system , machine learning , pattern recognition (psychology) , data mining , computer security , social science , botany , physics , sociology , chaotic , biology , programming language , thermodynamics
The smile detection approach is quite prominent with the face detection and thereby the enormous implementations are prevalent so that the higher degree of accuracy can be achieved. The face smile detection is widely associated to have the forensic of faces of human beings so that the future predictions can be done. In chaos theory, the main strategy is to have the cavernous analytics on the single change and then to predict the actual faces in the analysis. In addition, the integration of Principal Component Analysis (PCA) is integrated to have the predictions with more accuracy. This work proposes to use the analytics on the parallel integration of PCA and chaos theory to enable the face smile and fake identifications to be made possible. The projected work is analyzed using assorted parameters and it has been found that the deep learning integration approach for chaos and PCA is quite important and performance aware in the multiple parameters with the different datasets in evaluations.