What are the Applications of Computer Vision?

For millions of years, evolution worked tirelessly to improve the brain’s functions, resulting in the eventual formation of an advanced mechanism that works quickly and error-free. Vision is the most complex and least explored system of the brain. Scientists have not yet pinpointed exactly how visual information is processed by the brain’s visual cortex or what stages of analysis visual information goes through. 

That being said, scientists have succeeded in enabling machines to mimic the process of human visual cognition. The foundations for computer vision and image recognition goes back to the 1970s. However, it wasn’t until recently that computer vision found increasing application outside of labs and research centers. 

This powerful technology has found its way into various applications across numerous industries and has become an indispensable element of technological development and digital transformation. Let’s find out where computer vision technologies are applied and how they benefit businesses. 

What is computer vision?

Computer (machine) vision is a subsection of Artificial Intelligence (AI) that allows machines to understand and interpret images. Computer vision works much the same way as human vision. 

Human sight has the advantage of context and the ability to tell objects apart, how far they are, whether they’re still or moving, etc. Computer vision trains machines to perform these functions, but it depends more on algorithms, data, and cameras than on optic nerves, the visual cortex, and the retina. Roughly speaking, computer vision needs to carry out three subtasks – emulating the eye, emulating the visual cortex, and copying how our brain processes and responds to visual content.  

Like any other AI-enabled algorithm, computer vision needs massive amounts of data. It analyzes data over and over until it creates a pattern that allows it to recognize images. For example, to train a computer to identify cars, you need to feed it with many images of cars and car-related items to help it recognize one and learn the differences. 

Five applications of computer vision 

AI, ML, deep learning, and computer vision have transformed the future of many industries. All of us use solutions powered by computer vision algorithms knowingly or unknowingly. For example, we use FaceID to unlock our iPhones. Computer vision can also help us stay healthier when much of the world is still suffering from COVID-19. It can help track people in a particular area and detect whether they are following new social distancing norms or not. But there are many ways the world can benefit from computer vision. Here are the top five industries where computer vision has shown the most prominent results:

• Healthcare
• Transportation
• Retail
• Manufacturing 
• Agriculture 

Computer vision for healthcare 

The healthcare industry is one of the earliest adopters of computer vision technology and new automation solutions. Medical imaging data is one of the richest sources of information for doctors. But it has one significant drawback. Analyzing patient data requires hours of manual work. This technology can take the lion’s share of manual analysis off the backs of doctors so they can focus more on treatment with the right technology in place. 

Computer vision can analyze X-ray imaging and pick up on patterns that are far too subtle for the human eye. Computer vision can also help with CT scans and MRIs. It can easily detect internal bleeding, tumors, clogged blood vessels, etc. Moreover, computer vision can greatly reduce the time it takes to detect disease and identify even the slightest changes invisible to the human eye. AI-powered technologies can increase the accuracy of medical imaging data.

Computer vision is also used for skin and breast cancer detection. It helps to detect cancer in its earliest stages. The algorithm compares non-cancerous and cancerous cells to detect the disease. Though doctors still rely on manual analysis, computer vision can increase accuracy and automate many of the most cumbersome processes. 

Computer vision for transportation 

Self-parking and self-driving cars aren’t fiction in 2022. Computer vision is used to detect objects, analyze road signs, create 3D maps, and bring the idea of fully autonomous cars into reality. 

Self-driving cars analyze data from sensors and cameras to respond accordingly when situations arise on the road situation. Computer vision is also used in Parking Guidance and Information (PGI) systems. It’s a cheaper alternative to sensor-based technologies that require regular maintenance. Camera-based occupancy detection systems can assist drivers under any weather conditions. 

Along with self-driving and self-parking cars, computer vision can also help track and count freeway traffic. Thanks to modern technologies, we can design better traffic management systems and improve road safety. 

Computer vision for retail 

Configured cameras allow retailers to collect a high frequency of data to improve the customer journey and increase sales. Here’s where AI-enabled systems come in handy to analyze and make use of the collected data. 

With computer vision, fully autonomous shops have become a reality. Such systems can understand human interactions and monitor the movement of products. Self-service checkouts are entering the market at a blistering pace to solve some of the biggest pain points of the retail industry like long lines. Computer vision can perform many things like full inventory scans, story layouts, heat maps, stock-outs, etc.  

Computer vision for manufacturing

The manufacturing industry has already automated a wide range of processes. Computer vision can automate quality control, increase efficiency, and minimize risks. It’s hard to achieve a 100% rate of accuracy for large-scale manufacturing.

Cameras and computer vision can help detect micro and macro level defects more efficiently. Such systems help to minimize defects and decrease the costs of production. More and more companies are opting for automated product assembly lines where computer vision can track product components and maintain the highest manufacturing standards. 

Computer vision for agriculture

Computer vision and modern technologies have also changed the agricultural industry. Al-powered models are used for automated harvesting, weather forecasting and analytics, crop and yield management, and plant disease detection. The technology has gained a strong footing and is likely to expand and automate even more farming processes. 

Computer vision can be on guard and ready to detect even the slightest changes in crops due to disease or malnutrition. Technical advancements and computer vision can far surpass the traditional detection methods to maximize field efficiency. 

In conclusion 

Computer vision is used across a range of industries that rely on image and video data. It can help automate numerous mundane tasks, achieve higher accuracy, ensure safety, and maximize the efficiency of most business processes. With more and more companies adopting AI-enabled systems, computer vision will continue to expand and win over more industries. Contact us to discuss how your business can benefit from computer vision technologies.