𝐂𝐎𝐌𝐏𝐔𝐓𝐄𝐑 𝐕𝐈𝐒𝐈𝐎𝐍 is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models machines can accurately identify and classify objects and then react to what they "see".
It is the field of computer science that focuses on replicating parts of the complexity of the
human vision system and enabling computers to identify and process objects in images and videos.
𝑯𝑰𝑺𝑻𝑶𝑹𝒀 𝑶𝑭 𝑪𝑶𝑴𝑷𝑼𝑻𝑬𝑹 𝑽𝑰𝑺𝑰𝑶𝑵:

In the
1950s, using some of the first neural networks to detect the edges of an object and to sort simple objects into categories like circles.

In the
1970s, the first commercial use of computer vision interpreted typed or handwritten text using optical character recognition.

In the
1990s, making large sets of images available online for analysis, facial recognition programs flourished.
𝑪𝑶𝑴𝑷𝑼𝑻𝑬𝑹 𝑽𝑰𝑺𝑰𝑶𝑵 𝑾𝑶𝑹𝑲𝑰𝑵𝑮:

Acquiring an image

Processing the image

Understanding the image
𝑪𝑶𝑴𝑷𝑼𝑻𝑬𝑹 𝑽𝑰𝑺𝑰𝑶𝑵 𝑨𝑺 𝑨 𝑱𝑰𝑮𝑺𝑨𝑾 𝑷𝑼𝒁𝒁𝑳𝑬:
Computers assemble visual images like a jigsaw puzzle. All these pieces of the jigsaw are to be assembled into an image and that's how neural networks work for computer vision.
They distinguish many different pieces of the image, they identify the edges and then model the subcomponents. Using filtering and a series of actions through deep network layers, they can piece all the parts of the image together. the computer is often fed hundreds or thousands of related images for training and recognizing specific objects.
𝑨𝑷𝑷𝑳𝑰𝑪𝑨𝑻𝑰𝑶𝑵 𝑶𝑭 𝑪𝑶𝑴𝑷𝑼𝑻𝑬𝑹 𝑽𝑰𝑺𝑰𝑶𝑵:

Computer Vision for Defect Detection

Computer Vision for Intruder Detection

Computer Vision for Screen Reader

Computer Vision for Code and Character Reader (OCR)

Computer Vision in robotics for Bin Picking