Computer vision is a field of artificial intelligence (AI) that trains computers to see, interpret, and understand the visual world.
Using digital images from cameras and videos, computer vision models can identify, classify, and react to objects just like a human would.
A Simple Analogy: Digital Sight
Think of computer vision as giving a computer its own set of eyes and a brain.
The Eye: A camera or sensor
The Brain: An AI model processes that image, recognizes patterns, and derives meaning from it.
Just as your brain instantly tells you that you’re looking at a dog, computer vision allows a computer to do the same by analyzing pixels and features in an image.
How Does It Work?
The process generally involves feeding a computer a massive number of images. Using algorithms, particularly deep learning models called Convolutional Neural Networks (CNNs), the system learns to detect patterns and features.
For example, to teach a computer what a car is, you’d show it thousands of pictures of cars. The AI would learn to identify the common features—wheels, windows, headlights—until it can reliably recognize a car in a new, previously unseen image. This process includes tasks like:
Image Classification: What is the main subject of this image? (e.g., “This is a cat.”)
Object Detection: Where are the objects in this image? It draws a box around each one. (e.g., “The cat is here, and the dog is here.”)
Image Segmentation: Which pixels in this image belong to which object? It outlines the precise shape of each object.
Real-World Examples Computer vision is already a part of our daily lives:
Unlocking Your Phone 🤳: Facial recognition uses computer vision to identify the unique features of your face.
Self-Driving Cars 🚗: Vehicles use cameras and computer vision to “see” lanes, pedestrians, traffic signs, and other cars to navigate safely.
Medical Imaging 🩺: Doctors use it to analyze X-rays, MRIs, and CT scans to detect tumours or other anomalies more accurately.
Manufacturing 🏭: On an assembly line, it automatically spots defects like cracks, scratches, or missing components, ensuring product quality.
Retail 🛒: Cashier-less stores use it to track which items you pick up and put in your bag, charging you automatically as you leave.