Comments on using MLP and FFT for fast object/face detection

A fast neural nets for object/face detection are presented in [(S.Ben-Yacoub, 1997), (Beat Fasel, 1998) and (S. Ben-Yacoub et al., 1999)]. The speed up factor of these networks based on cross correlation in frequency domain between the input image and the weight of the hidden layer. But, these equations presented in [(S. Ben-Yacoub, 1997), (Beat Fasel, 1998) and (S. Ben-Yacoub et al., 1999)] for conventional and fast neural nets as well as speed up ratio are not valid for many reasons presented here. In this paper, a correct formula for the computation steps required for conventional, fast neural nets presented in [(S. Ben-Yacoub, 1997), (Beat Fasel, 1998) and (S. Ben-Yacoub et al., 1999)] and speed up ratio is introduced. Moreover, conventional neural nets are proved to be faster than those fast neural nets presented in [(S.Ben-Yacoub, 1997), (Beat Fasel, 1998) and (S. Ben-Yacoub et al., 1999)]. Practically, simulation results confirm this approval. Furthermore, only in case that the input image is symmetric or the weight are symmetric, neural nets presented in [(S. Ben-Yacoub, 1997), (Beat Fasel, 1998) and (S. Ben-Yacoub et al., 1999)] give correct result as conventional neural nets.