What is Computer Vision?
As humans we see things, work out what they are, and act on what we saw. Computer Vision is the domain of AI that gives a machine the same three steps.
1What it is
Eye and brain
Pick a domain and it rises. What is standing on the pedestal is the data that domain is fed. Drag sideways to turn.
Takes in visual information — photographs, video, camera and sensor images — analyses it, and makes a decision about what it sees. Its aim is to collect information from pixels.
Examples: Face unlock on a phone · Crop and pest monitoring by drone · Surveillance systems, self-driving cars
2Computer Vision vs Image Processing
This comparison has been asked in more than one paper, and the answer always turns on one word: superset.
| Computer Vision | Image Processing | |
|---|---|---|
| What it does | Extracts information from images or videos to infer meaning and understand them, so it can predict from the visual input | Processes the raw input images to enhance them, or to prepare them for other tasks |
| Which contains which | A superset of Image Processing | A subset of Computer Vision |
| Examples | Object detection, handwriting recognition | Rescaling an image, correcting brightness, changing tones |
Cleaning the page, and reading it
3Applications
- Facial recognition — security in smart homes, guest recognition, and attendance systems in schools.
- Face filters — Instagram and Snapchat identify the facial dynamics of a person through the camera and apply the selected filter.
- Google’s Search by Image — compares features of the input image against a database of images.
- Computer vision in retail — tracking customer movement through stores, analysing navigational routes, and inventory management by estimating stock from security camera footage.
- Self-driving cars — identifying objects, getting navigational routes and monitoring the environment.
- Medical imaging — creating and analysing images, assisting doctors with interpretation, and converting 2D scans into interactive 3D models.
- Google Translate app — point a camera at a sign; optical character recognition reads the image and augmented reality overlays the translation.
4From the board papers
(A) They are exactly the same. (B) Computer Vision enhances the image while Image Processing does not. (C) Computer Vision is a superset of Image Processing. (D) Image Processing is a superset of Computer Vision.CBSE board exam 2026
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(C) Computer Vision is a superset of Image Processing. Note that (D) is the same sentence the wrong way round, which is the trap. And (B) has it backwards — enhancing the image is what image processing does.
(a) Computer Vision; Image Processing (b) Machine Learning; Artificial Intelligence (c) Image Processing; Computer Vision (d) Object Detection; Image ProcessingCBSE sample paper 2025–26
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(c) Image Processing; Computer Vision. Option (a) is the same pair reversed. Read the blanks in order and check the word subset before choosing.
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Computer Vision is the domain of AI that works with visual data — images and videos — extracting information from pixels so the machine can understand what it is looking at. Examples: face recognition, object detection.
Natural Language Processing works with human language, written or spoken, so the machine can read or hear and make sense of words. Examples: chatbots, translation, spam filters.
The difference is what goes in: pixels for CV, language for NLP.
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1. It does not only create and analyse medical images — it acts as an assistant, helping doctors with the interpretation of what the images show.
2. It can read 2D scan images and convert them into interactive 3D models, letting medical professionals gain a far more detailed understanding of a patient’s condition.
5Check yourself
Which statement is correct?
Object detection and handwriting recognition are examples of:
Rescaling an image and correcting its brightness are examples of: