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Face detection using Zernike moments is presented in this work. Face detection is obtained in two steps. In the first step the image to be treated is presented to a program which calculate its Zernike moments vector with appropriate parameters. In the second step, this reduced vector is used as an entry on the input layer of a neural network, beforehand trained with similar vectors. The neural network provides on its output layer a vector of co-ordinates in (R,?) representing pixels surrounding the face contained in the treated image.
The Zernike moments are used here for there properties of orthogonality and rotational invariability. The
experimental results of the application of our method on images of the XM2VTS database are presented using a
new objective criteria for measuring performances.

Item Type	Journal
Divisions	» Faculty of Science and Technology
ePrint ID	35
Date Deposited	2014-10-30
Further Information	Google Scholar
URI	https://univ-soukahras.dz/en/publication/article/35

@article{uniusa35,
    title={Face detection using Zernike moments. Evaluation by quantitative measurement creterion},
    author={Mohammed Saaidia, S. Lelandais, V. Vigneron and M. Bedda},
    journal={WSEAS Transactions on Signal Processing., Issue 2, Vol. 3}
    year={2007},
    volume={},
    number={},
    pages={},
    publisher={}
}