Computer Vision, abbreviated as CV, is a domain of AI that depicts the capability of a machine to get and analyze visual information and afterward predict some decisions about it.
The entire process involves image acquiring, screening, analyzing, identifying, and extracting information.
This extensive processing helps computers to understand any visual content and act on it accordingly.
In computer vision, Input to machines can be photographs, videos, and pictures from thermal or infrared sensors, indicators, and different sources.
Computer vision-related projects translate digital visual data into descriptions.
This data is then turned into a computer-readable language to aid the decision-making process.
The main objective of this domain of AI is to teach machines to collect information from pixels.
Examples:-
Self-Driving cars/ Automatic Cars CV systems scan live objects and analyze them, based on whether the car decides to keep running or to stop.
Face Lock in Smartphones Smartphones nowadays come with the feature of face locks in which the smartphone’s owner can set up his/her face as an unlocking mechanism for it. The front camera detects and captures the face and saves its features during initiation. Next time onwards, whenever the features match, the phone is unlocked.