Combination of SVM, LDA, PCA and linear regression under fuzzy system in human face recognition

  • Authors

    • Bulbul Ahammad Daffodil International Universuty
    • Liton Jude Rozario Daffodil International Universuty
    • Anup Majumder Jahangirnagar University
    • Md. Imdadul Islam Jahangirnagar University
    2019-07-22
    https://doi.org/10.14419/ijet.v7i4.26010
  • Viola-Jones Object Detector, Fuzzy Rules, Surface Plot, Eigen Vector, RBF.

  • Abstract

    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.

     

     

  • References

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  • How to Cite

    Ahammad, B., Jude Rozario, L., Majumder, A., & Imdadul Islam, M. (2019). Combination of SVM, LDA, PCA and linear regression under fuzzy system in human face recognition. International Journal of Engineering & Technology, 7(4), 6970-6976. https://doi.org/10.14419/ijet.v7i4.26010

    Received date: 2019-01-16

    Accepted date: 2019-06-09

    Published date: 2019-07-22