Have you ever thought about how Facebook recognizes most of the people in a picture? how are you able to add a dog’s filter to your face on Snapchat? Well, these are just a few of the applications of computer vision systems.
The concept of Computer vision was first started in 1970. Today, it has become an instrumental part of our daily lives knowingly or unknowingly.
The advancement in the field of AI and ML has contributed greatly to the growth of computer vision in recent years, so much so that they are outdoing humans in tasks like objection detection, data analytics, etc.
What is Computer Vision?
Computer Vision, a subset of Artificial intelligence (AI) refers to designing and developing systems that are capable of capturing information from multidimensional visual data.
In simple terms, computer vision technology focuses on creating a system to replicate the complex functioning of the human visual system, thus enabling machines to recognize and track objects in videos and images. All the credit goes to deep learning and neural networks, for AI to evolve so much in recent years. It is one of the major technologies that bridge the gap between the digital and the physical world.
Did you know?
The computer vision market is expected to grow from USD 10.9 billion in 2019 to USD 17.4 billion by 2024-growing at a CAGR of 7.8%.
Applications of Computer Vision
Since the first computer vision breakthrough was made at the University of Toronto, the technology has been growing exponentially. Coupled with machine learning and neural networks, the potential of vision systems are limitless.
Here are some of the examples.
- The tech giant Google has implemented the Reverse Image search that is almost used by everyone at some point of time to search for similar images available on the web.
- Another US-based conglomerate, Apple unveiled the Face ID feature in 2017. Since then, it has undergone major advancement in terms of technology and sensors. Today, Face Id is used by millions of users worldwide for unlocking phones, accessing personal data, and making payments.
So, why vision system is gaining so much popularity? And the answer is; to reap the potential benefits of replacing humans with computers. It takes a lot of effort to train a system but once a computer learns how to do things, it can do it better than almost any human on earth.
One of the most famous applications of Computer Vision in the automotive sector is done by Tesla with their Autopilot system.
The automaker launched the driver assistance system back in 2014 with limited functionality. But now, with advanced Machine learning algorithms and image processing, it has evolved to a full-fledged auto-pilot system that is capable of driving you from your home to the supermarket with just a simple voice command.
Computer vision coupled with the right sensor can work wonders. Predictive analytics of machines, assembly of components, defect inspection systems, and quality control are some examples where computer vision technology can be implemented to optimize business processes.
Automobile manufacturers can employ an array of vision sensors to add advanced driver assistance functions like road sign detection, driver drowsiness detection, accident prevention systems, etc.
For mining companies, vision technology is being used to monitor underground equipment and mines to identify defects and damages before it could lead to any accident.
AI and ML prove to be beneficial for 3D printing companies. Computer vision with AI is used for in-depth scanning of multiple layers of an object to rectify errors. For 3D printing, machine learning predicts the behavior of the material in different physical conditions.
Another area where computer vision becomes imperative is a product inspection at pharma companies. Computer vision can automate the process of quality control before packaging. Every tablet has to pass through a specialized chamber with high-resolution cameras to identify defects using various image processing techniques.
Computer vision technology has made a splash in the finance sector as well.
Although the technology is yet to achieve its full potential, a few big players have already started using it in the onboarding of new customers.
For instance, Bank of America uses Artificial Intelligence for data analytics for effective fraud management and fake bill detection. With AI and fast analyzing power, the technology can deliver quick results and save the employees’ time.
In 2019, a bank started the service to withdraw money through ATMs using a face recognition system. The system can recognize 16,000 facial points to accurately verify the identity of a person.
Healthcare is a domain where computer vision can bring in some real value. While it cannot replace healthcare personnel, there is a good chance to assist in diagnostics that require a high level of expertise but do not contribute majorly to the final diagnostics.
One of the major challenges the healthcare system is facing is the huge amount of data being produced by patients every year. Microsoft is working to develop a tool that uses artificial intelligence to collect this data and process it to recommend treatment to patients based on their medical history and reports.
Computer vision has also changed farming practices to make them more effective and technology-driven. So, what exactly can computer vision bring to the table? It can offer solutions to monitor and maintain farm equipment and livestock efficiently and easily. Moreover, using deep learning & satellite imagery, farmers can estimate seasonal yield before harvesting directly from their smartphone or computer.
Computer vision can also enable various tasks from planting to harvesting the crops production cycle to be performed automatically.
As the vision technology continues to expand, the time is not far when the vision industry will take the first position as a solutions purveyor for real-world problems. Whether it is road-sign and signal detection in road transportation, advanced aerial mosaicing in the defense sector, or vision-based defect detection in production lines, computer vision has a lot to offer for every sector. The technology is, certainly, worth adopting to optimize business processes, add automation, strengthen security and manage traffic effectively.
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