A COMPREHENSIVE REVIEW OF THE HISTORY AND METHODS OF COMPUTER VISION

DOI: 10.31673/2412-4338.2025.011767

Abstract

Extended abstract: The purpose of this article is to explore the history, methods, applications, and usage of computer vision in modern society. It aims to find and describe the potential of computer vision and its pivotal role in shaping the future of technology and human interaction with the visual world. Article describes main methodologies of computer vision, including convolutional neural networks (CNNs), deep belief networks (DBNs), and autoencoders, describing their principles, functionalities, and main usages in image recognition and analysis. Through an in-depth exploration of methodologies and real-world applications, the article highlights the impact of computer vision across diverse domains. It discusses the usage of computer vision technologies through different industries such as autonomous vehicles, healthcare, security, augmented reality, and industrial automation. As a result, this article provides a comprehensive analysis of existing computer vision algorithms, describing their benefits and drawbacks in detail. It further explores the primary applications of these algorithms across various domains, illustrating the specific tasks for which each algorithm is optimally suited. In addition, the article delves into case studies and examples that highlight the practical implementations of these algorithms. Looking ahead, the future of computer vision holds the promise of groundbreaking advancements and innovative developments. These technologies are aimed to fundamentally transform methods of perceiving, interacting with, and comprehending the visual world, paving the way for unprecedented changes in numerous fields. The potential impact of these advancements suggests a significant shift in both the technological landscape and our daily lives, creating a new era of visual data processing and interpretation.

Keywords: computer vision, image recognition, machine learning, deep learning, artificial intelligence, neural networks.