<p>This paper presents a simple and fast recognition system with various facial expressions, poses, and rotation. The proposed system performed in two phases. Face detection is the first phase. The front and profile face detected cropped face area from the image by Viola-Jones algorithm and the right side face is detected from the image by taking the flip of the profile image. Principal component analysis (eigenfaces) algorithm is used in the recognition phase and depends on created database models used to be compared with test face image input to the recognition procedure. For training and testing the system, two sets of the image of the file exchange interface (FEI) database have been used to identify the person. The experimental result shows the effectiveness and robustness of the method used for the detection of the face and achieves high accuracy of 96%, which improves the recognition performance with low execution time. Furthermore, the accuracy of 35 trained images for recognition is 97.143% with average time execution which is (0.323657s). Also, the accuracy of 15 tested images for recognition is 93.315% with average time execution which is (0.3348s) which indicates a good and strong success and accuracy method for facial recognition.</p>

<span lang="EN-US">Recently, one of the most important biometrics is that automatically recognized human faces are based on dynamic facial images with different rotations and backgrounds. This paper presents a real-time system for human face tracking and recognition with various expressions of the face, poses, and rotations in an uncontrolled environment (dynamic background). Many steps are achieved in this paper to enhance, detect, and recognize the faces from the image frame taken by web-camera. The system has three steps: the first is to detect the face, Viola-Jones algorithm is used to achieve this purpose for frontal and profile face detection. In the second step, the color space algorithm is used to track the detected face from the previous step. The third step, principal component analysis (eigenfaces) algorithm is used to recognize faces. The result shows the effectiveness and robustness depending on the training and testing results. The real-time system result is compared with the results of the previous papers and gives a success, effectiveness, and robustness recognition rate of 91.12% with a low execution time. However, the execution time is not fixed due depending on the frame background and specification of the web camera and computer.</span>

In this paper, its enhancement of the Virtual digital message classifications, appreciation of its informal user interface design language, and outstanding information conception abilities. Unity of the most common reproduction responsibilities in digital communications is to assess the bit error rate (BER) of dial-up connection. The Formulation of the scintillation index obsessed on BER of Vortex Gaussian beam in a blustery atmosphere and originate by exploitation of the Huygens Fresnel Process to usage this structure and assess the normal bit error rate (BER), therefore it applies the ITU-R Method to find the Kolmogorov of structure constant parameter and Random Phase Screen Method. The scintillation index leaders of a multimode of Vortex Gaussian beam smooth, and used topological charge, by used zenith angle is started from zero to nighty degree. Furthermore, the typical signal-to-noise ratio (SNR) which is related to the scintillation index as against the BER is calculated via the log-normal method of the beam order. and it’s circulated in gradient path, which is presented for some parameters like it, source sizes, focal lengths and used unique wavelength, λ = 1.35μm. According to the one desired wavelength distribution is dealt with theoretically, the outcomes of BER Guesstimate were starting to the increased value of source size, the structure is better-quality and scintillation index, BER and the some of the factors are decreased the value of BER and enhanced the optical communication system.