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Go to Editorial ManagerA novel hiding system is proposed in this work which is based on Least Significant Bits (LSB) embedding of information such as speech in gray scale images. The proposed hiding algorithm embeds the secrete infonnation message bits in the least significant bits of the cover image pixels such that the number of secrete infurmation bits to he embedded in least significant bits of cover image pixel is variable and detennined randomly. So that cover image pixel may contain no secrete information bit, one bit, two bits , or three bits according to the pseudo random nwnber generator that generates integer numbers randomly between O and 3. The resulting image (the cover image within which the secret information is hidden) is called stego_image. Stego_image is closely related to the cover image and does not show any details of the secret infonnation. It ensures that the eavedroppers will not have any suspicion that message bits are hidden in the illll!ge and standard steganography detection methods can not estimate the locations in which the secret message bits are embedded and can not estimate the locations in which the secrete information bits are hidden nor the number of bits embedded in oover image . The proposed system achieves perfect reconstruction of the secret message.
Image segmentation is the process of automatically dividing an image into distinct, meaningful, and non-overlapping regions. The quality of the segmentation process determines the efficiency of other image processing tasks. Analyzing microstructural images is crucial since the mechanical properties are strongly dependent on the microstructural phases’ statistics. These images are considered one of the most difficult and challenging images to deal with due to their special characteristics, such as the convergence in pixels intensity values, overlapping in colors, boundaries and textures in phase regions, infinite shapes of grains and colonies, etc. As there is no generic technique suitable to be used with all microstructures, this work reviews techniques that have been effectively used and recommended to be employed in metallurgical research, with a brief description of their principles, advantages, and disadvantages, and discusses their applicability. The major aim of this work is to spare time and effort searching for and experimenting with all the available methods for future researchers.
Interest in neural networks as an alternative to the conventional algorithmic techniques has grown rapidly in recent years. Noise removal or noise suppression is an important task in image processing. In general, the results of the noise removal have a strong influence on the quality of the following image processing techniques. In this paper, two feed forward NN schemes have been presented for impulsive noise removal. The computation is reduced by using an artificial image in training. Results of NN schemes show high performance especially when the ratio of impulsive noise in testing are the same or greater than that of training image. The presented schemes are used for grayscale and also for truecolor.
A novel iterative method for the restoration of gray-scale blurred images is presented. The method is an enhanced modification of the Fixed-Phase Iterative Algorithm (FPIA). A blurred image is enhanced by Laplace operator during the FPIA method on each iteration. This modification is originally supported theoretically by a derivation of some iterative deblurring methods that are based on the enhanced version of the blurred image instead of the blurred image itself only. The modified fixed phase iterative algorithm (MFPIA) method is examined to restore some Gaussian-and motion-blurred gray-scale images. The restored Images via this proposed method are compared with the original FPIA method. From the comparison, it is apparent that the MFPIA method is better from human visual measurements point of view with less number of iterations. In addition to that benefit the restoration by the FPIA method results in images of bad quality even with high number of iterations.
The use of image communication has increased in recent years. In this approach, the encryption process is performed by hiding the processing steps of the wavelet transform. The attacker cannot obtain the original image unless processing steps are known. In this paper, the performance of three different hidden wavelet-based schemes are applied. First, hiding filter types encryption scheme (HFT), second, hiding wavelet packet tree encryption scheme (HWPT), lastly, by combining the previous two methods (HFTWPT). Several experiments are given to illustrate the performance of the proposed schemes.
The use of image communication has increased in recent years. In this approach, the encryption process is performed by hiding the processing steps of the wavelet transform. The attacker cannot obtain the original image unless processing steps are known. In this paper, the performance of three different hidden wavelet-based schemes are applied. First, hiding filter types encryption scheme (HFT), second, hiding wavelet packet tree encryption scheme (HWPT), lastly, by combining the previous two methods (HFTWPT). Several experiments are given to illustrate the performance of the proposed schemes.
Today, with the continuous increase in the use of computer networks and the rapid evolution of information technologies. The secure transmission of data over the Internet has become an urgent necessity to preserve the privacy of users and protect sensitive information from theft and distortion. images are most of this transferred data, so it was necessary to protect it by encrypting them using algorithms that ensure the protection of information access to the receiver. Color images contain sensitive information and details that must be secured and protected. This paper produces a comprehensive review of image encryption methods and classifies them based on various concepts such as chaotic maps, DNA, etc. with comparisons between existing approaches to accessing different security parameters. Additionally, the types of encryption keys were reviewed along with some common types of attacks and the most important methods for measuring encryption efficiency.
Architecture is writing, based on the understanding that writing is a disturbance of a creative medium and a stirring of its waters. In a practice where its deconstructive text reshapes its systems by breaking traditions and exploring formations that contradict reality, rearranging it according to a new image. It involves selecting specific data from among options that displace the form from its traditional compliance with function, towards producing architectural spaces occupied with developing their formal discourse, and then calling for their employment in forms that give their users feelings creating an experience and presenting an idea with a boldness of creation not approached by creativity before. The architectural form is disturbed, dispersed, and twisted, confusing our familiar image of buildings and presenting other faces, confirming architecture's ability to renew its creative discourse, differing from what is expected of it, enriching our visual experience with other experiments, renewing the vitality of reception, and sustaining the phenomenon of architecture's survival, as in the works of Daniel Libeskind, Zaha Hadid, Peter Eisenman, Frank Gehry, and Bernard Tschumi.
In this paper, image deblwring and denoising are presented. The used images were blurred either with Gaussian or motion blur and corrupted either by Gaussian noise or by salt & pepper noise. In our algorithm, a discrete wavelet transform is used to dJvide the image into two parts. This partition will help in increasing the manipulation speed of images that are of the big sizes. Therefore, the first part represents the approximation coefficients, that a blur is reduced b,y using the modified fixed-phase iterative algorithm. While the second part represents the detail coefficients, that a noise is removed by using the BayesShrink wavelet thresholding method.
Exceptionally strong press-hardened steels (PHS) are significantly demanded in the automobile industry for satisfying the carbon neutrality criterion. Recent research attempts to produce advanced-ultrahigh-strength medium steels have resulted in a variety of alloying approaches, thermomechanical processing techniques, and microstructural modifications for these steel grades. It has been shown that adding microalloying components to standard Mn-B steels can refine the microstructure of PHS which leads to better mechanical properties such as hydrogen embrittlement resistance and other performance indicators for service. In this paper a general review about the effect of microstructure test on the mechanical behavior of Press Hardening Steel (PHS) where microstructure approaches have also demonstrated good potential for the mechanical characteristics of PHS steel, in line with need for new evaluation and discovery meantime, statistical data of the microstructural phases heavily influence the mechanical properties, microstructural image analysis is essential. The purpose of this paper is to know how the microstructure phases will effect on the strength and hardness of press hardening steel also the alloying elements adding impact on the microstructure formulation and mechanical features of PHS.
This paper presents an approach for the recognition of off-line handwritten numeric strings using genetic algorithm. The proposed scheme is divided in two parts. The first part is remove the image noise, then the vertical projection is used to segment the numeric strings at isolated digits and every digit will be presented separately to the second part. The second part using improved genetic algori_thm to recognize isolated handwritten digit. The result of the recognition of the numeric strings will display at the exit of the global system.
In this paper, a Neural Network (NN) model system for self-organization fish school system is identified. Monitoring and data extraction from fish school video has been achieved by using image processing technique in order to generate the data suitable for parameter identification of NN model system. Data obtained have been used to identify the parameters of a model based on a black-box represented by nonlinear autoregressive exogenous model (NARX). The obtained results show that this system can be used for multi robot formation system.