Abstract

Computer vision is a fast-growing field of artificial intelligence. It allows machines to understand and respond to visual information. This article gives a thorough overview of the basics, common image processing techniques, and the move toward deep learning methods like convolutional neural networks and vision transformers. Key computer vision tasks—such as classifying images, detecting objects, and segmenting them into parts—are explored in depth. The chapter also shows how this technology is used in different areas of life, like self-driving cars, healthcare, farming, and smart cities. The authors also look at recent trends like edge computing, multimodal AI, explainability, synthetic data, and low-shot learning. Along with these, they analyze the critical ethical and governance challenges they present. This article explains the technical foundations and societal implications of computer vision. It aims to provide readers with a comprehensive understanding of the field's potential and responsibilities in shaping the future of intelligent systems.