Computer vision is a field of artificial intelligence (AI) that enables computers and machines to interpret, understand, and derive meaningful information from visual inputs such as images, videos, and real-time streams. It mimics human vision by using cameras, data, and algorithms instead of biological eyes and brains, allowing machines to "see," analyze, and make decisions based on visual data
. Key aspects of computer vision include:
- Visual Perception: Capturing and comprehending visual information from cameras and sensors.
- Image Understanding: Recognizing objects, scenes, people, and their relationships within images or videos.
- Pattern Recognition: Identifying recurring shapes, textures, colors, and features in visual data.
- Machine Learning and Deep Learning: Using neural networks and algorithms to automatically learn and extract features from images, significantly improving accuracy over time
Computer vision has broad applications across industries such as healthcare (medical imaging), automotive (autonomous vehicles), manufacturing (defect detection), retail (product recognition), agriculture (crop monitoring), security (facial recognition), and entertainment (augmented reality)
. Historically, computer vision began in the 1960s with the goal of enabling machines to "see" and describe their environment. It evolved through advances in algorithms, image processing, 3D modeling, and neural networks, reaching accuracy levels today that often surpass human capabilities in tasks like object detection and classification
. The market for computer vision technology is rapidly growing, projected to reach hundreds of billions of dollars globally within the next decade, reflecting its expanding role in modern technology and business
. In summary, computer vision is the science and technology that teaches machines to understand and act on visual information much like humans do, but with greater speed and scale
