One of the simplest ways to understand a machine vision system is to consider it the "eyes" of a machine. The system uses digital input that's captured by a camera to determine action. Businesses use machine vision systems in a variety of ways to improve quality, efficiency and operations. What is Machine Vision And How Is It Used In Business Today? How do machine vision systems work?
FREMONT, CA: Machine vision is one of the important additions to the manufacturing sector. It has provided automated inspection capabilities as part of QC procedures. Nevertheless, the world of automation is becoming more complex with time. With rapid developments in many different areas, such as imaging techniques, robot interfaces, CMOS sensors, machine and deep learning, embedded vision, data transmission standards, and image processing capabilities, vision technology can benefit the manufacturing industry at multiple different levels. New imaging techniques have brought new application opportunities.
According to MIT neuroscientist Mriganka Sur, half of the human brain is devoted to vision. I'm no neuroscientist, but I imagine that there are two reasons: First, vision is extremely valuable: humans use it constantly, and for an endless variety of tasks, from reading to navigation to creating all manner of objects. Second, vision is a hard problem, considering all of the things that we're able to discern visually--under widely varying and often very challenging conditions, such as glare and low light. Computer vision enables machines to understand things through visual inputs, sometimes even exceeding the capabilities of human vision. For decades, computer vision has been a niche technology, because computer vision equipment has been large, expensive, and complex to use.
Retail innovations like Amazon Go have captured the headlines recently, but over the past few years, Computer Vision applications and technologies have been successfully integrated into the CRM domain, from sales and marketing to customer assistance and retention. Computer Vision can be a force multiplier in retail, providing valuable insights into customer behavior and aiding both upselling and cross selling. It can add essential information to a customer's profile based on visual data from smart telematic devices, a game-changer for insurance and utility companies. It can also help predict issues before they happen, allowing customer care teams to avoid dissatisfaction and churn. When a customer reaches out to a company with a technical or service issue, Computer Vision can effectively route the case to the relevant agent, and help the employee diagnose and resolve the problem much faster than if they were relying on voice or text alone.
The field of Machine learning is experiencing exponential growth today, especially in the subject of computer vision. Today, the error rate in humans is only 3% in computer vision. This means computers are already better at recognizing and analyzing images than humans. Decades ago, computers were hunks of machinery the size of a room; today, they can perceive the world around us in ways that we never thought possible. The progress we've made from 26% error in 2011 to 3% error in 2016 is hugely impactful.