The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

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

A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

Between the duality of sound and image, the completeness of the actor’s personality at the director comes to announce the birth of the appropriate theatrical role for that character as the basic and inherent element of the artwork, within his working system in the pattern of vocal behavior as well as motor/signal behavior as he searches for aesthetic and skill proficiency at the same time.
This is done through the viewer’s relationship with the theatrical event, which the director considers as an area of active creative activity in relation to (the work of the actor) through vocal recitation and the signs it broadcasts in order to fulfill the requirements of the dramatic situation and what it requires of a visual vision drawn in t

NAA Mustafa, University of Sulaimani, Ms. c Thesis, 2010 - Cited by 4

تحلل الورقة الحالية تمثيل كاريل تشرشل للصورة النمطية للمرأة في Top Girls (1982). تُظهر المسرحية كيف وصلت النساء في نضالهن لمحاربة اضطهاد الرجال عبر التاريخ ، إلى مستوى من القوة والحرية يستخدمان للسيطرة على جنسهن دون شفقة. مارلين ، الشخصية المركزية في هذه المسرحية ، هي امرأة تبنت الصفات الذكورية إلى أقصى الحدود. لتسلق سلم النجاح إلى قمته ، تضحي مارلين بطفلها وعائلتها وحبها. كما تعرض المسرحية النساء الصامتات والم

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