Computer vision is a branch of computer science that allows machine systems to see, process, and interpret visual information in real-time.
At the beginning of the 20th century, computer vision was an unrealistic dream for scholars and engineers. Back in the 1960s, the Summer Vision Project, which was assigned to undergrads, first talked about developing a computer system that will interpret the stimuli from the surroundings and respond accordingly. Another trace in the history of computer vision is provided by Larry Roberts. His thesis, ‘Machine perception of three-dimensional solids’ outlined how to “extract 3D information from 2D images or objects.” Later in the 1980s, David Marr published “Vision.
A Computational Investigation into the Human Representation and Processing of Visual Information,” which was also one of the discoveries in the history of computer vision. Since then, rigorous studies were conducted by many scientists and engineers in the field. Finally, in the 1990s, due to cheaper, high-powered supercomputers, engineers working on computer vision redirected their focus to mathematical models. With continued research and refinement, computer vision was transformed from an unrealistic idea or expectation to practical reality. But, what exactly is computer vision all about?
Computer vision: the concept
Computer vision is nothing but a scientific field that allows computers to capture, interpret, understand, and process the objects that are visually perceivable. With the help of Artificial Intelligence (AI) and deep learning models, computer vision systems are able to understand the captured digital images and react suitably. Today, several industries are benefitting from computer vision technology. Computer vision systems serve myriad purposes, ranging from predictive maintenance to quality control and on-site safety.
Computer vision: the advantages
Let’s now move on to understanding how computer vision systems benefit business users. Having the ability to see and interpret, computer vision systems automate several tasks without needing human intervention. As a result, business users can enjoy benefits like:
Faster and simpler process – Computer vision systems can carry out monotonous, repetitive tasks at a faster rate, making the entire process simpler. Accurate outcome – It’s no secret that machines never make any mistake. Likewise, computer vision systems with image-processing capabilities will commit zero mistakes, unlike humans. Ultimately, products or services provided will not only be quick but also of high quality. Cost-reduction – With machines taking up responsibilities of performing cumbersome tasks, errors will be minimized, leaving no room for faulty products or services. As a result, companies can save a lot of money that would be otherwise spent on fixing flawed processes and products.
Computer vision: the limitations
No technology is free from flaws. And the same applies to computer vision systems. Let’s now look at a few limitations that the technology inherently has: Lack of specialists – Computer vision technology involves the use of AI and ML. To train a computer vision system powered by AI and ML, companies need to have a team of professionals with technical expertise. Without them, building a system that can analyze and process the possible surrounding details is not possible. Need for regular monitoring – What if a computer vision system breaks down or has a technical glitch? To ensure that doesn’t happen, companies have to get a dedicated team onboard for regular monitoring and evaluation.
Despite their current limitations, computer vision systems can bring companies immense opportunities to increase revenue streams, meet productivity goals, and streamline work processes. However, we have barely just scratched the surface of computer vision capabilities. The future is yet to be seen.
