How is computer vision transforming modern-day enterprise?
Today, we have reached the autonomous aspect of technology where we are starting to talk about self-driving vehicles and other autonomous systems. But ever think how autonomous systems are becoming possible? Computer vision plays a vital role in this scenario, making computer systems more capable of understanding their surroundings. One of the most popular applications where computer vision is being leveraged is self-driving cars. It allows vehicles to classify and spot different objects. This technology is capable of deciphering, analyzing and excerpting meaningful data from images or a series of images faster and more accurately than humans.
As an innovative field of artificial intelligence, the concept of computer vision was first introduced in the 1970s. The technology then was very limited in use. But it has gained much interest when the first significant breakthroughs in computer vision were made at the University of Toronto in 2012. The most exciting factor behind the growth of this technology is the amount of data we generate today that is then used to train and make computer vision better.
Today, this technology is used by big firms worldwide across areas, ranging from autonomous driving and retail to healthcare, in order to improve tasks and boost productivity.
How Does Computer Vision Works?
As the crucial field of computer science, computer vision processes, assesses and makes sense of visual data – images and videos – as much as in the same way humans do. It enables computers to automatically perform the tasks such as processing an image at a pixel level and understanding it. Computer vision algorithms that are in use today are based on pattern recognition. For instance, if someone sends bulk images of flowers, the computer examines them, recognize patterns that are similar to all flowers and then create a model flower.
In general, computer vision systems perform object classification, object identification, and object tracking.
Real-World Applications of Computer Vision
Businesses across industries, including manufacturing, retail and automotive, are exploring and experimenting with computer vision systems to strengthen quality control in factories, engage customers, and enhance the safety of autonomous and connected vehicles.
Today, every industry and business is using facial recognition systems for surveillance and security systems. These systems are powered by computer vision that helps identify suspicious behavior. Even Facebook’s technology that identifies people to tag in photos also uses computer vision. This technology can provide a new level of control by analyzing the real-time video stream and recognizing the objects and people around.
Managing paper-based documents is a critical and complex task for businesses. As it is a time-consuming process, it contains valuable insights. This is where computer vision has a role to play, performing accurate detection and narrowing down target objects to deliver key insights that a human may take years to uncover. Optical character recognition, a branch of computer vision, primarily enables a computer to recognize the letters of the scanned document. Healthcare organizations, insurance companies, law firms, and financial institutions use this technology for document scanning.
Predictive Maintenance and Quality Control
Since CV systems make things more efficient, effective and safer, they can be used in predictive maintenance to spot issues before any breakdowns occur. It can also be used in quality control measures. Predictive maintenance refers to the process of thwarting the failure of equipment, by evaluating data throughout production to find unusual behavior ahead of time, ensuring appropriate measures to avoid extended periods of production downtime.
With an increasing need for safety, quality inspection and automation, the demand for computer vision technology will continue to grow. According to the report, the market for computer vision is predicted to reach US$17.4 billion by 2024, at a CAGR of 7.8 percent throughout the projected time frame of 2019-2024.