In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

This paper presents a proposed method for (CBIR) from using Discrete Cosine Transform with Kekre Wavelet Transform (DCT/KWT), and Daubechies Wavelet Transform with Kekre Wavelet Transform (D4/KWT) to extract features for Distributed Database system where clients/server as a Star topology, client send the query image and server (which has the database) make all the work and then send the retrieval images to the client. A comparison between these two approaches: first DCT compare with DCT/KWT and second D4 compare with D4/KWT are made. The work experimented over the image database of 200 images of 4 categories and the performance of image retrieval with respect to two similarity measures namely Euclidian distance (ED) and sum of absolute diff

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

   In this study,  depleted uranium concentrations were calculated  in  sediments  Diyala River samples , where 14 samples of sediment along the Diyala River were collected , starting from the Rustumiya area and ending with the Tuwaitha area after its confluence with the River Tigris , using the solid - state nuclear track detectors technique (SSNTDs).        We found that the highest concentration of depleted uranium was in the sample (A-13), and was taken from the Tuwaitha area with the specific activity of the amount (78.1 ± 8.5 Bq/kg ) and the lowest concentration of the depleted uranium was in the sample  (A-7), and was taken from the Azwaip area with  the

???? ?? ??? ????? ???? ?????? ?????????? ????? ??????? ???? ?????? ????? ??? ??? ????? ?? ???? ??? ????? ????? ???? ????? ????? ?? 0-3cm, 10cm, 20cm, 30cm, 40cm ???????? ????? ?? ???? ????? ???????? ?? ???? ????? ?????? CR-39??????? ?? ??? ??? ?????????? ???????????? ???????? ???? n.cm-2.s-1 5 x 103?? ?????? ?????????? Am241- Be??? ???? ??????? ????????? ??? ?? ???? ????? ?????????? ??? ?? ????? ??????? ?????? 0.881±0.086??? ?? ??????? ????? ??? ????? ??? ?? ????? ????? ??? ???????? ???0.441±0.036 ??? ?? ???????