Computer vision is a field of Artificial Intelligence that is used to train the computers so that they can interpret and obtain information from the visual world such as images. Hence, computer vision uses AI technology to solve complex problems such as image processing, object detections, etc.

Computer vision is a field of artificial intelligence (AI) that focuses on enabling computers to interpret and understand visual information from the real world. It involves the development of algorithms and techniques that allow machines to extract meaningful insights from digital images or videos, much like humans do with their visual senses.

The primary use of computer vision in AI is to empower machines to perceive, analyze, and interpret visual data, leading to a wide range of applications across various industries. Some common applications include:

Object Detection and Recognition: Computer vision algorithms can detect and identify objects within images or videos, enabling applications such as automatic surveillance, autonomous vehicles, and augmented reality.
Image Classification and Categorization: These algorithms can classify images into predefined categories or labels, allowing for tasks such as content moderation in social media, medical image analysis for diagnosis, and quality control in manufacturing.
Facial Recognition: Computer vision systems can identify and verify individuals based on their facial features, leading to applications in security systems, access control, and personalized user experiences.
Gesture Recognition: By analyzing hand movements and gestures in images or videos, computer vision can enable interfaces for controlling devices through gestures, such as in gaming, virtual reality, and human-computer interaction.
Medical Imaging: Computer vision techniques assist in analyzing medical images such as X-rays, MRIs, and CT scans, aiding in diagnosis, treatment planning, and disease monitoring.
Autonomous Navigation: Computer vision is crucial for enabling robots and autonomous vehicles to perceive and understand their surroundings, allowing them to navigate safely and make informed decisions in dynamic environments.
Document Analysis and OCR: Optical character recognition (OCR) systems, a subset of computer vision, extract text from images or documents, facilitating tasks such as digitizing printed documents, automated data entry, and document indexing.
Visual Search: Computer vision powers visual search engines that allow users to search for similar images or products based on visual similarity rather than textual queries, enhancing e-commerce, image retrieval, and creative inspiration platforms.

Overall, computer vision plays a vital role in bridging the gap between the physical world and digital systems, enabling machines to comprehend and interact with visual information in ways that were once exclusive to human perception.