A Digital Magazine from IT Department

Computer Vision-By Ashish Palandurkar

Computer vision is an artificial intelligence field that teaches computers to interpret and comprehend images. Machines can properly recognise and classify objects using digital images from cameras and videos, as well as deep learning models, and then react to what they “see.”

Computer vision systems can be utilised for a variety of activities, including the following:

Classification of objects. The system analyses visual content and assigns a category to each object in a photo or video. The system, for example, can find a dog among all the items in an image.
Object recognition. The system parses visual content and identifies a particular object on a photo/video. For example, the system can find a specific dog among the dogs in the image.
Object tracking. The system processes video finds the object (or objects) that match search criteria and track its movement.

How does computer vision work?
Computer vision technology tends to mimic the way the human brain works. But how does our brain solve visual object recognition?

Our brains rely on patterns to decode individual objects, according to one prominent theory. Computer vision systems are built using this principle.
Pattern recognition is the foundation of today’s computer vision algorithms. We train computers on a massive amount of visual data—computers process images, label objects on them, and find patterns in those objects. For example, if we send a million images of flowers, the computer will analyze them, identify patterns that are similar to all flowers and, at the end of this process, will create a model “flower.” As a result, the computer will be able to accurately detect whether a particular image is a flower every time we send them pictures.

Where may computer vision technology be used?
Some individuals believe that computer vision is a design technology from the far future. This is not the case. Many aspects of our lives have already been influenced by computer vision. Below are just a few notable examples of how we use this technology today.

Computer vision systems already help us organize our content. Apple Photos is an excellent example. The app has access to our photo collections, and it automatically adds tags to photos and allows us to browse a more structured collection of photographs. What makes Apple Photos great is that the app creates a curated view of your best moments for you.

Ashish Palandurkar, Assistant Professor, IT Department