Hazem M. El-Bakry and Qiangfu Zhao
Fast ObjectFace Detection Using Neural Networks and Fast Fourier Transform
3748 - 3753
2007
1
11
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/3384
https://publications.waset.org/vol/11
World Academy of Science, Engineering and Technology
Recently, fast neural networks for objectface
detection were presented in 13. The speed up factor of these
networks relies on performing cross correlation in the frequency
domain between the input image and the weights of the hidden
layer. But, these equations given in 13 for conventional and fast
neural networks are not valid for many reasons presented here. In
this paper, correct equations for cross correlation in the spatial and
frequency domains are presented. Furthermore, correct formulas for
the number of computation steps required by conventional and fast
neural networks given in 13 are introduced. A new formula for
the speed up ratio is established. Also, corrections for the equations
of fast multi scale objectface detection are given. Moreover,
commutative cross correlation is achieved. Simulation results show
that subimage detection based on cross correlation in the frequency
domain is faster than classical neural networks.
Open Science Index 11, 2007