Page 296 - AI Computer 10

6 6 Computer Visionision
Computer V

u Applications of Computer Vision u Convolutional Network
u Tasks Involved in Computer Vision u Neural Network
u Fundamental Concepts of Images u Deploying a CNN
u Open Source Computer Vision u No-Code AI Tools For Computer Vision

Computer Vision is a vital domain of Artificial Intelligence. It is a digital technology which is used for teaching machines
how to see and perceive the world, similar to as humans do. Computer vision can be defined as the domain of AI that
enables computers to analyse meaningful information from images, videos, and other visual inputs.
A human being sees an object through eyes. The eyes generate the visual signals into elctro-chemical signals that are
sent to the brain through the network of neurons. The brain recieves the signals, processes them, and creates the
image of the object. It then matches the image with the memory. If a match is found, the brain sends the output of
a recognised object with the proper label. If the image is not found in the memory, the brain tries to generalise with
the available information and produces the closest match, else it stores the image of the object for future reference.

Computer Vision works in a similar way. A Computer Vision model captures images of an object with the help of a
digital device, such as a camera or webcam, converts the image into digital signals, and passes them to the processing
unit (GPU or Graphics Processing Unit). The GPU performs all computations on the input signals and tries to match the
information with the stored dataset to come up with the closest match as output.

APPLICATIONS OF COMPUTER VISION

Using images from cameras and videos, deep learning models enable machines to accurately identify and classify the
objects. The various applications of Computer Vision are as follows:
u Manufacturing: In the manufacturing industry, the closely allied field of
machine vision has long been used for automated inspections, identifying
defective products on the production line, and for remote inspections of
pipelines and equipment. The technology is also used to automate and
optimise operational and control processes, by flagging inconsistencies or
anomalies.

162
162