In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

      Recently, digital communication has become a critical necessity and so the Internet has become the most used medium and most efficient for digital communication. At the same time, data transmitted through the Internet are becoming more vulnerable. Therefore, the issue of maintaining secrecy of data is very important, especially if the data is personal or confidential. Steganography has provided a reliable method for solving such problems. Steganography is an effective technique in secret communication in digital worlds where data sharing and transfer is increasing through the Internet, emails and other ways. The main challenges of steganography methods are the undetectability and the imperceptibility of con

Media studies have focused mostly on the issue of the mental image because the image that is formed in the mind has become not only a photo of a human being and having kept for himself. This image has an outside influence which may sometimes up to the formation of the fate of others and it sometimes includes individuals and groups together.
This study comes in the context of identifying the image of Iraqi political parties among Iraqi university students and the nature of the view that students have in their minds about these parties.
Chapter one includes the problem of the research, the importance of the study, the goals and method used. Chapter two is divided into two sections: section one deals with the concept of the mental i

In this work, we are obviously interested in a general solution for the calculation of the image of a single bar in partially coherent illumination. The solution is based on the theory of Hopkins for the formation of images in optical instruments in which it was shown that for all practical cases, the illumination of the object may be considered as due to a self – luminous source placed at the exit pupil of the condenser , and the diffraction integral describing the intensity distribution in the image of a single bar – as an object with half – width (U0 = 8 ) and circular aperture geometry is viewed , which by suitable choice of the coherence parameters (S=0.25,1.0.4.0) can be fitted to the observed distribution in various types of mi

In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca