A Short Review on Computer Vision: Visualizing the World Through Machine

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Abstract

Computer vision is a critical artificial intelligence component that enables machines to interpret and make decisions based on visual data. As we move towards an era where machines are increasingly responsible for decision-making, vision becomes a fundamental sensory modality for machines to perceive and understand their environment. The ability of machines to "see" and comprehend the world through visual input raises the question of whether they can truly grasp complex situations based on the objects and interactions within their surroundings. This paper provides a comprehensive exploration of the core concepts and algorithms underlying computer vision, starting from its early stages of development. It delves into foundational techniques, discussing their evolution and innovations shaping the field. Additionally, the paper addresses the inherent limitations of these foundational concepts and explores how they have influenced the development of current technologies. A critical analysis of present-day technologies is also provided, highlighting their challenges and limitations despite significant advances. Finally, the paper explores the wide-ranging applications of machine vision across various domains and the promising future prospects for the continued advancement of computer vision technologies.

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