Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd  level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet

عملية تغيير حجم الصورة في مجال معالجة الصور باستخدام التحويلات الهندسية بدون تغيير دقة الصورة تعرف ب image scaling  او image resizing. عملية تغيير حجم الصورة لها تطبيقات واسعة في مجال الحاسوب والهاتف النقال والاجهزة الالكترونية الاخرى. يقترح هذا البحث طريقة لتغيير حجم الصورة باستخدام المعادلات الخاصة بمنحني Bezier وكيفية الحصول على افضل نتائج. تم استخدام Bezier curve في اعمال سابقة في مجالات مختلفة ولكن في هذا البحث تم استخد

There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

     In this paper, we introduce an approximate method for solving fractional order delay variational problems using fractional Euler polynomials operational matrices. For this purpose, the operational matrices of fractional integrals and derivatives are designed for Euler polynomials. Furthermore, the delay term in the considered functional is also decomposed in terms of the operational matrix of the fractional Euler polynomials. It is applied and substituted together with the other matrices of the fractional integral and derivative into the suggested functional. The main equations are then reduced to a system of algebraic equations. Therefore, the desired solution to the original variational problem is obtained by solving the resul

The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

      The Costing Accounting is one the analytic tools which plays important role by support the management in planning&  control and decisions-making ,as it became attendant necessity to establish any project whether industrial ,commercial ,service or agriculture ..etc.

     The consolidated accounting system has committed the companies to have their active costing system in which the management can obtain their own data, but we found most of the economic units face problems of applying the costing system because of reasons related to the system design itself or might be related to the requirements of the application success.   

      Restoration is the main process in many applications. Restoring an original image from a damaged image is the foundation of the restoring operation, either blind or non-blind. One of the main challenges in the restoration process is to estimate the degradation parameters. The degradation parameters include Blurring Function (Point Spread Function, PSF) and Noise Function. The most common causes of image degradation are errors in transmission channels, defects in the optical system, inhomogeneous medium, relative motion between object and camera, etc. In our research, a novel algorithm was adopted based on Circular Hough Transform used to estimate the width (radius, sigma) of the Point Spread Function. This algorithm is based o

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material