The goal of fusing multi-focus images is to obtain one image that has all the significant features from each input. The fusion process is needed because of the limitations of the optical lens depth of field that is used to capture images, so images of various focused regions are produced. In this paper, a multi-focus image fusion algorithm is proposed. It is based on utilizing the biorthogonal wavelet transform to extract details and edges from the input images by making the approximation subband equal zero and applying an inverse transform to get images that have only edges, lines, and details. The average gradient metric, which is used to represent sharpness and clarity, is calculated as an activity measurement for each NxN block

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

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 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 importance of this research has been to rationalize the cost of producing maize seeds through the followers of modern techniques and methods in agricultural activities such as genetic engineering for the purpose of increasing production efficiency of maize seeds as well as the importance of calculating seed cost rationalization through the ABC system and thus rationalizing government spending. The research is based on a single hypothesis that the use of genetic engineering on corn seeds works to:increase production efficiency of seeds and savings in agricultural inputs, calculation of rationalization through the cost system on the basis of activity ABC The research reached a number of conclus

Abstract

The study aims to reveal the level of inclusion of citizenship values in the English language textbooks (We Can) series for elementary education in the Kingdom of Saudi Arabia. To achieve this objective, the "content analysis" methodology was used. A content analysis card was designed to include (6) main areas of citizenship values, it consisted of (28) sub-indicators of citizenship values that were supposed to be included in the English language textbook series (We Can) for elementary education. The study sample consisted of all the English language textbooks (We Can) series for elementary education, which consisted of (6) textbooks, two for each class. The results of the study indicated that there is a

ABSTRACT Background: work-related musculoskeletal disorders represent an important occupational health issues among dentists especially neck and low back complaints. Biomarkers of tissue damage as results of occupational physical demands could be used for detection of work related musculoskeletal disorders. Aim: The aim of this study was to assess work- related musculoskeletal disorders, physical work load index, selected salivary biomarkers (Creatine kinase and C - reactive protein) and to find the relation among them. Subjects and Methods: Study participants are consisted of 112 dentists. They were selected from college of dentistry /Baghdad University, health care center in Bagdad city. They were of both gender and aged between 40-45 yea