The Future of Computer Vision Technology


Computer vision technology is one of the fastest-growing markets in the tech world. Experts estimate the market will reach $49 billion by the end of 2022. This technology is used today mainly for facial recognition, for things like unlocking smartphones to go online and look at the latest Super Bowl lines, or the funny face filters that can be seen in your favorite social media software. 

During the pandemic of 2020, businesses have made rapid advances, with technology now available that was set to happen in the next several years. This trend isn’t slowing down anytime soon, with even more changes expected to occur in this sector in the near future. The applications of AI-powered computer vision are endless and will play a significant role in real-time analysis and insights within the business world. 

What is Computer Vision?

AI-enabled computer vision is the technology that lets computers see and comprehend their surroundings and make intelligent decisions based on these understandings. Professionals in this field must also find ways to teach computers to recognize videos and images, which is done through machine learning or coding. It augments and automates human sights in computers which helps businesses do things like improving security, automate surveillance, and execute efficiency in operations. 

Different types of computer vision depend on what is trying to be identified, with the computer looking at text, images, or faces. The ability to comprehend text is called OCR, or optical character recognition, which may be used for either typed or handwritten documents. 

Object detection can be used in robots and is used in many manufacturing processes that detect objects and recognize them. It can be a system as simple as a sensor that recognizes if an item has passed through. It’s also used in developing systems for robots required to identify and handle objects. 

One of the most important systems in self-driving cars uses image recognition technology that can figure out what images are and decide what to do depending on what the situation calls for. For example, a car’s system must decide what to do if it recognizes a pedestrian by analyzing whether or not it’s a threat to the moving vehicle. 

What’s the future?

There are an endless number of applications for computer vision technology. As a result, demand will increase for systems that are more user-friendly than the complicated training tools that are used today. It’s similar to how the internet altered the workforce with the use of PCs. This involves users implementing low-code tools and simpler interfaces that let developers create processes and automate them with little or no prior training. 

In the future, computer vision will be everywhere, with innovations in smartphones, PCs, laptops, and vehicles set to be unveiled. The newest computer vision software is optimized for scenarios that use low data in situations where hardware space is limited. This means a lot of the processing can be done with all the useless content filtered out. 

There’s no doubt that computer vision is set to play a significant role in future business and industries, from private institutions to government entities. For example, the banking sector will use different computer vision technologies to process and analyze various banking-related tasks. Whether preventing cybercrime, protecting real-time transactions, or detecting fraud, the use of computer vision technology will be crucial. 

Computer vision will also be used more frequently in the supply chain, as it helps companies limit errors and unnecessary waste during the production stage. Not only do things like faulty packaging affect profits, but they also have significant environmental effects. 

AI-based computer vision technology will become part of an increasing number of businesses moving towards more automation as the market for AI platforms will go beyond the $50 billion mark in the next few years. However, looking at the way it’s used in today’s technology, much of that growth will be attributed to computer vision technology. 

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