How Does Computer Vision Help Companies See New Opportunities?
Computer vision sounds dangerous. It immediately conjures up images of The Terminator or RoboCop. An out-of-control robot that is using some form of computer vision to destroy cities and enemies. Robot movies have been a Hollywood staple for a century now.
The reality remains exciting, although perhaps not as destructive as the movies. Using visual systems to process information can be an extremely useful and efficient way for many businesses to operate and this tech can work across almost any industry.
There are multiple types of business problem that can be solved by a computer vision system, including:
- Recognizing and classifying objects into groups: retail is a great example – computer vision can scan shelves and identify stock levels or search for specific items.
- Segmenting and verification of objects: comparing an object – such as a face – to a baseline is a good example of segmentation. For example, sentiment analysis for customers on video calls – were they mainly happy or angry?
- Recognizing text or written documentation: scanning written documents and drawing out important data, such as numbers or figures for human analysis or checking.
- Tracking people or object movement on video: video tracking for security is a good example – such as security cameras protecting a building site being able to recognize that an unauthorized human is on the site.
Computer vision is an offshoot of artificial intelligence (AI) – it’s a practical application of the underlying systems that drive AI. The image is the input into the AI system which can then analyze it based on the rules and requirements for a specific solution.
Broadly speaking, computer vision allows machines to interpret and make decisions based on visual data – like human sight but with the potential for vastly superior accuracy and speed.
The famous Amazon stores without any cashier or checkouts are another example. It is the sophisticated computer vision systems monitoring what shoppers pick up that make this possible. The system automatically charges customer accounts as they walk out of a store – no waiting to pay. Digital advertising can also display adverts targeted at the people walking past in real-time, gauging the age, gender, and even the mood of passersby, tailoring content accordingly.
Quality control in manufacturing has long been a painstaking task where a mistake early in a production line can be very expensive to rectify later on. Catching manufacturing problems early is at the heart of quality methods such a Six Sigma or the Toyota Way.
Now, with computer vision, anomalies on assembly lines can be detected with remarkable precision, ensuring that products meet exacting standards while substantially reducing human error. This not only bolsters product quality but also can lead to significant cost savings – catch problems early.
Computer vision can also analyze drone and satellite imagery to asses property values or size – useful for local government when planning property taxes and also the real estate industry.
Healthcare is another area where computer vision has been offering doctors an automated second opinion. Computer vision aids radiologists in spotting anomalies in medical imagery, sometimes catching what the human eye might overlook. Early diagnosis, enhanced by this technology, could mean the difference between a treatable condition and a life-threatening one. It’s not the end of doctors, but it is a powerful tool for creating a second opinion.
One of the most discussed areas of computer vision at present is self-driving and autonomous vehicles. Vehicles equipped with an array of sensors use computer vision algorithms to interpret their surroundings, making split-second decisions that can prevent accidents and guide a car – and passengers – safely to its destination.
Therefore, it is clear that computer vision has applications across many different industries, but it is rarely an out-of-the-box solution. Substantial sources of data are needed for training and this can lead to privacy concerns.
The data that computer vision systems collect, especially in public spaces, can be deeply personal, raising concerns about surveillance and personal data misuse. As businesses race to integrate computer vision into their operations, a parallel emphasis on ethical considerations and regulatory frameworks will be crucial.
Computer vision is revolutionizing many diverse sectors, from retail to healthcare. As the technology matures, its integration into modern business practices is likely to deepen, offering companies many new ways to enhance efficiency, reduce costs, and deliver unparalleled value to their stakeholders.
IBA Group has deployed many computer vision systems using a range of infrastructure, processing, and storage services. Click the link for examples.