The beginning of COVID-19 in Wuhan, China in late December 2019 and its worldwide transmission has led the World Health Organization to formally address the pandemic. The pandemic has imposed influential impacts on different environmental, economic, social, health, and living aspects. Publishing in scholastic journals was not immune from these impacts.

The effect of using three different interpolation methods (nearest neighbour, linear and non-linear) on a 3D sinogram to restore the missing data due to using angular difference greater than 1° (considered as optimum 3D sinogram) is presented. Two reconstruction methods are adopted in this study, the back-projection method and Fourier slice theorem method, from the results the second reconstruction proven to be a promising reconstruction with the linear interpolation method when the angular difference is less than 20°.

     Storing and transferring the images data are raised in recent years due to requisiteness of transmission bandwidth for considerable storage capacity. Data compression method is proposed and applied in an attempt to convert data files into smaller files. The proposed and applied method is based on the Wavelet Difference Reduction (WDR) as considered the most efficient image coding method in recent years. Compression are done for three different Wavelet based Image techniques using WDR process. These techniques are implemented with different types of wavelet codecs. These are Daub2+2,2 Integer Wavelet transform, Daub5/3 integer to integer wavelet transform, and Daub9/7 Wavelet transform with level four. The used mu

Biological image edge detection preserving the important structural properties in an image. Detecting accurate edges are very important for analyzing the basic properties associated with a biological image. Gradient operator plays very important role in edge detection. In this paper the images had been using are color biological images taken from microbiology laboratory at the biological department college of science Al-MustansiriyhUniversity and the effect of gradient operation have applied on around 10 different biological color images but view only two. In our proposed approach comparative of various gradient of biological image include (gradient of image, gradient of image using first order derivative edge detection (Soble,Prewitt,Ro

FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

A new de-blurring technique was proposed in order to reduced or remove the blur in the images. The proposed filter was designed from the Lagrange interpolation calculation with adjusted by fuzzy rules and supported by wavelet decomposing technique. The proposed Wavelet Lagrange Fuzzy filter gives good results for fully and partially blurring region in images.
 

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

     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

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

     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 pro