AI has been revolutionizing our day to day lives in more ways than we could imagine. One of the newest entrants to the club is Computer Vision.
Computer vision, commonly abbreviated as CV, is a subset of artificial intelligence. It deals with the way computer systems are able to infer data from digital images or videos.
Acquiring, processing, and extracting information from the images are some of the primary tasks of computer vision.
Many times, the terms image processing and computer vision are used interchangeably.
Image processing works to improve the image. It works on making the image more readable.
Computer vision, on the other hand, works with all types of visual input. It could be as one static image or a series of images in a video.
Computer vision works to extract information from the input rather than making the input more readable.
Computer Vision finds applications in several fields. Let’s discuss some of the most popular applications here.
Applications of Computer Vision Technologies in Different Industries
Autonomous vehicles are the future of commuting. It is expected to bring down the number of accidents as the possibility of human error is minimized.
Tesla’s self-driving vehicles are known to all. The company claims that its cars use eight cameras around the vehicle for a 360-degree view.
These cameras, which have a viewing range of up to 250m, use computer vision to render the road and traffic around the car. Using this data, the vehicle safely navigates on the road and reaches the destination.
Google’s self-driving car project, Waymo is another real-time application that makes use of computer vision. It uses data from live camera feeds from the car as well as various sensors to autonomously drive the car.
Computer vision is being used extensively in various parts of our healthcare systems. Healthcare depends a lot on imaging, extracting information, and recognizing trends from images.
In the COVID pandemic, Computer vision is being used more than ever to detect pneumonia in the X-Ray reports of patients.
Medical imaging can sometimes be tricky, with the images not being entirely clear. Hence, using an AI application helps in the correct diagnosis.
Robotics is one field that has been making good use of computer vision.
Autonomous robots and drones use cameras and sensors to navigate and avoid obstacles. The AI software in robots helps them perform their duties.
Autonomous Robots such as AnyMal or Spot by Boston Dynamics, are capable of working in oil and gas processing plants.
Using a variety of sensors and cameras, they are able to navigate to the various regions of the plants autonomously.
The insurance industry is one of the highest human-intensive industry. The insurance surveyor has to physically inspect the damages to release or reject the claim made.
Nowadays, insurance companies are using computer vision to analyze images from the incident. This helps speed up the process of claims processing.
Computer vision can seamlessly detect the origin of the incident and qualify it as genuine or fake. It can also detect doctored images so that fraudulent claims are filtered automatically.
Insurance companies are making good use of computer vision since it is beneficial to them. They are saving a substantial amount by not paying out fake claims.
Moreover, the customers of genuine claims are also benefitted as they get a quick resolution and payout.
The retail industry leverages computer vision technologies to a great extent.
Retail giants like Amazon have been using computer vision technologies for automatic billing.
In their store, Amazon Go, customers do not have to stand in line for billing. They are tracked with cameras that can identify which customer has picked up what item or kept back.
ScanItAll from StopLift is one checkout vision system that retailers have been using to ward off shoplifting or employee theft.
It seamlessly integrates with the pre-fitted ceiling security cameras to track shoppers and employees.
Upon encountering miscreants, the system notifies the management about the incident, which can then take further action.
The agriculture industry is recently witnessing a lot of technological advancements. This is owing to the recent rise in demand for food and crops as a whole.
With mass farming, it is a challenge to manage everything manually. Thus, the agriculture industry is making use of computer vision.
Farming activities such as harvesting and weeding are being conducted with the help of computer vision.
An AI-enabled tool is used to detect good quality crops to harvest and any growing weeds to pluck them. This improves the overall quality of the product and consumes less time.
Moreover, in agricultural processing, computer vision is used to detect good quality products from the total produce. This helps in faster segregation.
The banking industry uses computer vision extensively these days with the rise in fraud and counterfeit currency cases.
The banking system uses AI-based solutions to identify counterfeit currency being infused into the system at the customer touchpoints.
With these, banks, along with the police, can track the source of the counterfeits much sooner.
Using computer vision, washed cheques, and fake cheques can be spotted easily which is not quite visible to the naked eye.
Banking security systems also use AI-based software to detect suspicious behavior as well as monitor their employees.
The manufacturing industry uses computer vision mainly for quality control of the finished goods.
This can range from clothing, shoes, furniture, automobiles, FMCG products, electronics, etc.
Computer vision can easily detect defects that the naked eye cannot. This helps in manufacturing the highest quality products.
Moreover, tracking of the finished products with the help of barcodes uses computer vision.
Employee movement and tracking can also be performed with computer vision. This is necessary, especially in high-risk industrial zones, to ensure all personnel’s health and safety.
Computer vision is the new entrant to the AI ecosystem. It has already found many applications and uses across functions and industries.
Both enterprises and people are using computer vision. As more time passes, computer vision will develop more and will find increased applications. It can also perform more complex tasks.
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