Design and implementation a prototype system for fusion image by using SWT-PCA algorithm with FPGA technique

The technology of fusion image is dominance strongly over domain research for recent years, the techniques of fusion have various applications in real time used and proposed such as purpose of military and remote sensing etc.,the fusion image is very efficient in processing of digital image. Single image produced from two images or more information of relevant combining process results from multi sensor fusion image. FPGA is the best implementation types of most technology enabling wide spread.This device works with modern versions for different critical characteristics same huge number of elements logic in order to permit complex algorithm implemented. In this paper,filters are designed and implemented in FPGA utilized for disease specified detection from images CT/MRI scanned where the samples are taken for human's brain with various medical images and the processing of fusion employed by using technique Stationary Wavelet Transform and Principal Component Analysis (SWT-PCA). Accuracy image output increases when implemented this technique and that was done by sampling down eliminating where effects blurring and artifacts doesn't influenced. The algorithm of SWT-PCA parameters quality measurements like NCC,MSE ,PSNR, coefficients and Eigen values.The advantages significant of this system that provide real time, time rapid to market and portability beside the change parametric continuing in the DWT transform. The designed and simulation of module proposed system has been done by using MATLAB simulink and blocks generator system, Xilinx synthesized with synthesis tool (XST) and implemented in XilinxSpartan 6-SP605 device

Design and implementation of smart electronic solar tracker based on Arduino

Demand of energy increases in the global and exponential exhaustion is favored of resources by fossil fuel for electricity production with the new systems development. Compared with all other remainder energies, the specialist sun energy is the most bountiful energy and it's typically easy to be changed into electrical energy. The main thing of using solar panel is to produce electrical energy from sun's energy but the optimum energy can be generated by tracking solar panel due to the sun movement from east to west. The problem can be solved by proposed systems where the sun tracking by solar panel that based on high intensity of sun ray.  This paper concentrates on tracking the sun by using servo motor coupled with solar panel. So that, the largest quantity of sun light at the incident panel along the day at any time is better than that for method of fixed panel array which is less efficient. The microcontroller Arduino (mode UNO) was programmed by using C++ language while the track of sun light processing was implemented by using light depending resistor (LDR), Chip IC H-bridge and microcontroller Arduino (UNO) circuits have been designed by using Proteus software. By circuit design and sun tracking control process, the cost reduction has been improved and high amount of energy was saved when implemented this system

Establishment Network by Using FSO Link Based on MD Code for Hybrid SCM-SAC-OCDMA Wireless System

Since the wireless systems are working under nature environments and influenced by turbulence, weather in Iraq that leads to extended amount of fading signal, dissipation or attenuation. Basic “hybrid Subcarrier Multiplying Spectral Amplitude Coding (SCM-SAC) of Optical Code Division Multiple Access (OCDMA)" indoor or outdoor optical system depends on generally “Multi-Diagonal (MD)" security code by using optical space known as “Free Space Optic (FSO)" that was proposed in this work. It is found that the mention hybrid wireless systems can be used in operating mesh networks. The main proposed idea of hybrid optical technique was analyzed and simulated by normally taking into simulation account that the directly effecting by rain and haze attenuations. In addition, there are mention and description for atmospheric effects, FSO mesh network, modulation scheme, simulation, and the data security. From simulation results, the hybrid system using MD code produces reduced “bit-error rate (BER)" at heavy storm rain to distance or range of 500 m and at drizzle rain up to 2500 m range. And also investigates the performance of using the proposed system with radio over fiber (RoF) for UWB signals through indoor propagation in building applications of wireless channel

Text Hiding in Coded Image Based on Quantization Level Modification and Chaotic Function

A text hiding method in codded image is presented in this paper that based on quantization level modification. The used image is transformed into wavelet domain by DWT and coefficient of transform is partitioned into predefined block size. Specific threshold has been used to classify these blocks into two types named smooth and complex. Each type has its own method of text hiding (binary data), for smooth blocks, secret bits which represent the text data are switched by the bitmap. In order to reduce distortion, the quantization levels are modified. To reach extra embedding payload the quantization level could carry extra two bits depending on other threshold. The complex block carry one data bit on each block and quantization levels are swapped to reduce distortion with bitmap flipping. The proposed method result shows a high signal to noise ratio, with studying capacity as important in this work

Electroencephalogram Based Stress Detection Using Extreme Learning Machine

The detection of stress is important because it contributes to diverse pathophysiological changes including sudden death. Various techniques have been used to evaluate stress in terms of questionnaire or by quantifying the changes of physiological signals. Electroencephalogram signals are highly useful in measuring human stress. Therefore, to solve and detect stress problem, this work had extracted electroencephalogram features of theta, alpha, and beta bands in the frequency domain by wavelet packet transform because these bands are concerned with stress. In this research four features have been supplied to extreme learning machine which gave accuracy of 98.56% of detecting stress from normal state based on db4 with an average sensitivity of 92.52% and specificity of 95.88%. This research studied the stress on 15 students due to mathematical exercises in a noisy environment with different stimulus