Artificial Intelligence for Image Processing and Analysis

Abstract

A large number of persecutors have been interested in computer vision research. It evolves from the collection of raw data to the development of techniques and ideas that combine digital image processing, model recognition, machine learning, and computer graphic design in order to achieve a more complex result. The desire to work across a broad spectrum of disciplines and fields has drawn a large number of academics in recent years. With reference to recent technological and theoretical concepts, this paper provides an explanation of the development of computer vision, specifically in relation to the processing of images in various areas of their field application, as well as the future of computer vision. In order to find information in images and videos, such as information on events or descriptions, as well as picture patterns, students can use computer vision to analyze them. This was accomplished through the application of multi-purpose application domain methods in conjunction with large-scale data analysis. With its introduction to computer vision, image processing, and related studies, this paper makes a significant contribution to the most recent reviews in these fields by providing a broad overview of the field. To make things easier to understand, we divided the mainstream of computer vision into four categories: picture processing, object recognition, and machine learning, respectively (among others). Artificial intelligence (AI) has made significant strides in the fields of X-ray, ultrasound, computed tomography (CT), and other types of medical imaging in recent years. Many artificial intelligence-based tools are currently being developed to automate the analysis of medical images and to improve the accuracy of automatic image interpretation, both of which are important goals. Image analysis combined with the consistent face recognition factor enables readers to comprehend the effectiveness of the system and respond appropriately in situations where improvisation is required. Image analysis combined with the consistent face recognition factor with this study, the authors hope to provide readers with a comprehensive understanding of the problem while also opening up new avenues for further investigation.