Computer Vision Fundamentals
How machines 'see' — from pixels to object detection.
Inspired by learning material from Google
Computer vision lets machines interpret images and video.
Images are numbers
An image is a grid of pixels, each with color values. To a computer, a photo is just a large array of numbers.
Convolutional Neural Networks (CNNs)
CNNs slide small filters across an image to detect patterns — edges first, then textures, then whole objects. They're the workhorse of vision.
Common tasks
- Classification: what is in this image?
- Object detection: where are the objects (bounding boxes)?
- Segmentation: which pixels belong to which object?
Real-world uses
- Medical imaging diagnosis
- Self-driving car perception
- Quality inspection in manufacturing
- Photo search and tagging
Key takeaways
- Images are numerical grids of pixels.
- CNNs detect patterns from simple to complex.
- Vision powers everything from medicine to self-driving cars.