It turns out that something most people take for granted, namely the ability to see, process, and act on visual input, is extremely difficult to replicate in machines. That is exactly what computer vision (CV) aspires to achieve. While not as advanced as human vision, computer vision has progressed to the point where it is now very useful in business. Here’s more on what computer vision is and how it’s applied in the workplace.

What is computer vision?

Computer vision refers to the process by which a computer can recognise and process images (photos, videos, etc.) using artificial intelligence algorithms, and then generate an appropriate output from the analysis because the computer can “understand” the content. Computer vision, in particular, can classify, identify, verify, and detect objects. Machine learning technology, in particular, the iterative learning process of neural networks, and significant leaps in computing power, data storage, and high-quality yet inexpensive input devices, have aided recent advances in computer vision.

Three main components are there to computer vision.

  1. Get the image: When a digital camera captures an image, it creates a digital file that is made up of zeros and ones.
  2. Process it: Algorithms are used to extract basic geometric elements from binary data in order to create images.
  3. Analyze and comprehend: The data is analysed in the final step of computer vision. The images are then used to make decisions using high-level algorithms.

The difficulties of replicating that ability in machines were underestimated because even the tiniest of humans can process and understand images. What appeared to be a straightforward problem turned out to necessitate decades of investigation. The visual world is complex, and much remains unknown about how human vision works and how the brain processes visual information.

Despite the fact that computer vision companies has overcome many obstacles to date, there are still obstacles to overcome depending on what computer vision is used for and the data it can acquire. Computer vision requires a lot of data processing power and memory, and the quality of the images/data can affect the results. Computer vision is still being optimised for all applications by computer scientists.

Computer vision usage in business

There are a plethora of uses for the ability to extract meaning from “seeing” visual data. Computer vision can be used in conjunction with other technologies like augmented and virtual realities to expand capabilities.

Face recognition, which is based on computer vision, is used in surveillance and security systems, as well as the technology behind Facebook’s “tag” feature. In China, facial recognition technology is used in police work, payment portals, and other applications. Even retail stores use the technology to keep track of inventory, track customers through the store, and allow customers to pay for items on their bill using facial recognition technology instead of using the cash register.

Many car companies, including Ford and Tesla, are racing to get their autonomous vehicle into mass production. Computer vision is a crucial technology that enables self-driving cars. Autonomous vehicles’ systems process visual data continuously, from road signs to seeing vehicles and pedestrians on the road, before deciding what action to take.

In medicine, computer vision aids in the diagnosis of disease and other ailments, as well as extending surgeons’ vision during operations. There are now smartphone apps that use the phone’s camera to diagnose skin conditions. In fact, X-rays, scans, and other image-based data account for 90% of all medical data, and much of this data can now be analysed using algorithms.