Efficient technique to estimate age using PCA & multi SVM classification

  • Authors

    • Laiphrakpam Jibanpriya Devi
    • J L Mazher Iqbal
    2017-12-28
    https://doi.org/10.14419/ijet.v7i1.2.8999
  • Facial Images, SVM, PCA Algorithm, Age Estimation, Multi SVM.

  • Abstract

    Human interaction with computer is recent trend in computer technology. In order to obtain age information, image-based age estimation systems have been developed using information from the human facial images. We develop a new technology which identify the characteristic of human being like age. Facial information study will lead us to identify age. While generic growth patterns that are characteristics of different age groups can be identified. In order to create an accurate algorithm for age classification, we build an appropriate datasets for training is build using SVM classification method. We build an application base on MATLAB software to estimate age based on the trained data. Feature of face is extracted using PCA method and stored the data in array matrix. The accuracy of the trained data is 95.65%. We have an average matching percentage of 92%. We have Euclidean distance calculation method to verify the matched data and we found 100% verified.

  • References

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  • How to Cite

    Jibanpriya Devi, L., & Mazher Iqbal, J. L. (2017). Efficient technique to estimate age using PCA & multi SVM classification. International Journal of Engineering & Technology, 7(1.2), 81-84. https://doi.org/10.14419/ijet.v7i1.2.8999

    Received date: 2018-01-01

    Accepted date: 2018-01-01

    Published date: 2017-12-28