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We present in this communication a new method to localize a face in an image. The originality of work presented consists on the use of vectors of geometrical moments like entries to a Forward Back-Propagation neural network which provide at its output layer a vector of co-ordinates in (R,?) representing pixels surrounding the face contained in the treated image. Very known for their orthogonality and their
rotational invariability, the geometrical moments of Zernike are calculated here to form the feature vectors
supplied to the input layer of the network. The experimental results of the application of our method on images
of the XM2VTS database are presented.

Item Type	Conference
Divisions	» Faculty of Science and Technology
ePrint ID	50
Date Deposited	2014-10-30
Further Information	Google Scholar
URI	https://univ-soukahras.dz/en/publication/article/50

@inproceedings{uniusa50,
    title={Face detection by neural network trained with Zernike moments},
    author={Mohammed Saaidia, S. LELANDAIS, V. VIGNERON and E.M. BEDDA},
    year={2007},
    booktitle={The 6th WSEAS International Conference on Signal Processing, Robotics and Automation (ISPRA\'07)}
}