Skin detection is very challenging because of the differences in illumination, cameras characteristics, the range of skin colours due to different ethnicities and many other variations. New effective and accurate methodologies are developed for skin colour detection to easily identify human's skin colour threw databases which are specifically designed to assist research in the area of face recognition. One of these is the recently built SFA database that showed high accuracy for segmentation of face images. The approach described in this paper exploits skin and non-skin samples provided by SFA for skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Most importantly, the scheme proposed tries to segment facial colour images inside or outside SFA by means of skin samples belonging to SFA. Simulation results in both SFA and UTD colour face databases indicate that detection rates higher than 95% can be achieved with either measure.

In this paper, the leaky acoustic microwaves (LAW) in a piezoelectric substrate (Lithium Niobate LiNbO3 Cut Y-X) were studied. The main method for this research was classification using a probabilistic neural network (PNN).The originality of this method is in the accurate values it provides. In our case, this technique was helpful in identifying undetectable waves, which are difficult to identify by classical methods. Moreover, all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity were classified in order to build a model from which we could easily note the Leaky waves. Accurate values of the coefficient attenuation and acoustic velocity for Leaky waves were obtained. Hence, in this study, the focus was on the interesting modeling and realization of acoustic microwave devices (radiating structures) based on the propagation of acoustic microwaves

Laser communication between satellites in the constellation and from the satellites to ground stations offers a gigantic data rate for the users. This principal advantage drives telecom companies to develop this technology to use it like a carrier signal, the most disadvantage of this technology is the need to very complicated pointing systems between the transmitter and the receiver due to a very small beam divergence, continually moving of satellites in orbits and the distance between the satellites (tens of thousands of kilometers). The laser beam suffers continuously from several factors like atmospheric turbulences, internal and external vibrations. All these factors lead to an increase in the bit errors rate and cause degradation in the communication quality. This paper deals with a new method of modelisation of external effects in transmission of signal light from a ground station to the satellite through atmospheric disturbances. Indeed, an in-depth investigation, of the influences of satellite vibrationsinlaser signal transmission between satellites constellation, has been conducted by studying the effect of the intensity of vibrations on the optical signal amplitude. Some solutions are proposed to improve the efficiency of optical satellites communications.

Skin detection is very challenging because of the differences in illumination, cameras characteristics, the range of skin colours due to different ethnicities and many other variations. New effective and accurate methodologies are developed for skin colour detection to easily identify human's skin colour threw databases which are specifically designed to assist research in the area of face recognition. One of these is the recently built SFA database that showed high accuracy for segmentation of face images. The approach described in this paper exploits skin and non-skin samples provided by SFA for skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Most importantly, the scheme proposed tries to segment facial colour images inside or outside SFA by means of skin samples belonging to SFA. Simulation results in both SFA and UTD colour face databases indicate that detection rates higher than 95% can be achieved with either measure.

The resonant frequencies and bandwidths of the inverted rectangular patch over anisotropic substrates are investigated in this paper. A rigorous analysis is performed using dyadic Green’s function formulation in the vector Fourier transform domain. The Galerkin’s technic is then used in the resolution of the integral equation; the complex resonance frequencies for the TM01 mode are studied with sinusoidal basis functions. The numerical results obtained are compared with previously published numerical results computed by means of the electromagnetic simulator “IE3D software”. Good agreement is found in all cases among all sets of results. For an isotropic substrate, it is confirmed that the bandwidth decreases with increasing of air-gap layer for high permittivity and low thickness of the substrate. Also, we show that the resonant frequencies and bandwidths are highly dependent on the permittivity variations alongside the optical axis. Other theoretical results attained display that the resonant frequencies downtrend monotonically with increasing substrate thickness, the diminution being larger for the uniaxial anisotropy of the substrate. Finally, numerical results for the effects of uniaxial anisotropy in the substrate on the radiation of the inverted rectangular microstrip structure are also presented.