Combination of SVM, LDA, PCA and linear regression under fuzzy system in human face recognition Article Swipe
Related Concepts
Pattern recognition (psychology)
Artificial intelligence
Support vector machine
Linear discriminant analysis
Facial recognition system
Principal component analysis
Fuzzy logic
Computer science
Face (sociological concept)
Linear regression
Regression
Machine learning
Mathematics
Statistics
Sociology
Social science
Bulbul Ahammad
,
Liton Jude Rozario
,
Anup Majumder
,
Md. Imdadul Islam
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.14419/ijet.v7i4.26010
· OA: W4401048458
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.14419/ijet.v7i4.26010
· OA: W4401048458
One of the main applications of image processing is recognition of human face. In this paper, we worked on several benchmark databases of human face to identify a person based on Linear Regression, SVM (Support Vector Machine and Viola-Jones Object detector), LDA (linear discriminant analysis) and PCA (Principal Component Analysis). All the four methods are combined under Fuzzy system and we get the accuracy of 96.4% which is higher than any individual method. Â
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