Computer vision originated from an MIT undergraduate project in the 1950s using early neural networks to detect object edges and categories. It involves acquiring, processing, analyzing, and understanding digital images to extract data about the real world. Computer vision builds algorithms that can understand image content and apply it to other uses. It works through techniques like image segmentation, object detection, and feature matching. Computer vision has many real-world applications including optical character recognition, machine inspection, medical imaging, automotive safety, and fingerprint recognition.