Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other. In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect presence of hidden image. Measures calculations of SNR, SNR segmental, SNR spectral, MSE and correlation show that, audio music cover file (2channales) is the safest uses as arrier with replace the 9 number of LSB without noticeable noise. Bits of secret message can be hiding capacity reach up to 28 % of the total music cover audio size and the three type's measures of SNR are 32, 28 and 31 dB. For speech cover audio the replacing LSB is safely uses at LSB bits number 6, where the hiding capacity is reach up to 37 % of size speech cover audio at 37, 36 and 39 dB for three type's measures of SNR. Correlation of cover samples was did not effected as a result of hiding secret image, where its value is up to 0.99 for all hiding operations.
Background: Acute appendicitis is regarded as one of the most common inflammation that needs surgical intervention. Different scoring systems have been used for diagnosing of acute appendicitis. ALVARADO score is one of the most widely used score in diagnosing of acute appendicitis, but the accuracy of the latter is insufficiently low in Middle-East patients. Thus a new scoring system called RIPASA score has been designed for diagnosing of acute appendicitis in those patients. The aim of this study is to use RIPASA score and compare its result with ALVARADO score in diagnosing of acute appendicitis.
Subjects and Methods: The study includes 200 patients with symptoms and signs of
... Show MoreThis study investigated a novel application of forward osmosis (FO) for oilfield produced water treatment from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). FO is a part of a zero liquid discharge system that consists of oil skimming, coagulation/flocculation, forward osmosis, and crystallization. Treatment of oilfield produced water requires systems that use a sustainable driving force to treat high-ionic-strength wastewater and have the ability to separate a wide range of contaminants. The laboratory-scale system was used to evaluate the performance of a cellulose triacetate hollow fiber CTA-HF membrane for the FO process. In this work, sodium chloride solution was used as a feed solution (FS) with a concentratio
... Show MorePan sharpening (fusion image) is the procedure of merging suitable information from two or more images into a single image. The image fusion techniques allow the combination of different information sources to improve the quality of image and increase its utility for a particular application. In this research, six pan-sharpening method have been implemented between the panchromatic and multispectral images, these methods include Ehlers, color normalize, Gram-Schmidt, local mean and variance matching, Daubechies of rank two and Symlets of rank four wavelet transform. Two images captured by two different sensors such as landsat-8 and world view-2 have been adopted to achieve the fusion purpose. Different fidelity metric like MS
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreIn this paper, an efficient method for compressing color image is presented. It allows progressive transmission and zooming of the image without need to extra storage. The proposed method is going to be accomplished using cubic Bezier surface (CBI) representation on wide area of images in order to prune the image component that shows large scale variation. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, bi-orthogonal wavelet transform is applied to decompose the residue component. Both scalar quantization and quad tree coding steps are applied on the produced wavelet sub bands. Finally, adaptive shift coding is applied to handle the remaining statistical redundancy and attain e
... Show MoreThe meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
... Show MoreThe digital image with the wavelet tools is increasing nowadays with MATLAB library, by using this method based on invariant moments which are a set of seven moments can be derived from the second and third moments , which can be calculated after converting the image from colored map to gray scale , rescale the image to (512 * 512 ) pixel , dividing the image in to four equal pieces (256 * 256 ) for each piece , then for gray scale image ( 512 * 512 ) and the four pieces (256 * 256 ) calculate wavelet with moment and invariant moment, then store the result with the author ,owner for this image to build data base for the original image to decide the authority of these images by u
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