Today’s machines not only perform tasks but also “see” and understand their surroundings the way humans do. We are not talking about sci-fi movies, but artificial intelligence has made the machines capable of “seeing” their surroundings.

This ability of AI has become a game-changer in various industries, accelerating progress with an unprecedented level of automation and efficiency at lightning speed.

In this article, we will go through the various aspects of computer vision and its use cases in everyday life. Let’s begin with the basics.

What is Computer Vision?

Computer vision technology is the subfield of artificial intelligence and machine learning. It lets machines understand and interpret visual data from their surroundings like humans. With computer vision, the aim is to bring automation to repetitive tasks that human intelligence can’t achieve. It enables the machines or computers to analyze, interpret, and make decisions as per the visual input.

With computer vision, the machines don’t just see things but understand the context and make sense of what is being seen. That’s why it has use cases in various industries, from healthcare to manufacturing to security and transportation.

Applications of Computer Vision

Computer vision helps overcome the limitations of human beings and achieve new standards of accuracy, precision, and dependability in visual tasks. Machines built with computer vision don’t get tired and offer high precision and efficiency in jobs of repetitive visual inspection. Furthermore, the human employees will also be exonerated to work on more creative and responsibility-demanded tasks. Here are some key world use cases of computer vision:

Manufacturing and Production

The factories have got more competent with technologies like computer vision in machines. It is aiding many tasks, including product inspection and damage detection. There were repetitive tasks in identifying defective products, thus bringing automation to reduce human-prone errors and incorporate both machine and human intervention for higher efficiency.

E.g. in the automotive industry, Tesla has redesigned the manufacturing processes to be a balance between machines and humans. The inspection systems have computer vision and can identify defects for human auditors to review.

Computer vision also helps with cycle time control, as machine vision systems can learn and measure each manufacturing cycle. It can be accomplished by 3D vision monitoring, which allows the AI system to create an accurate production process model while identifying any deviations from the standard.

On assembly lines, computer vision oversees automation for quality control. Computer vision offers high accuracy in identifying products for irregularities or defects as they come off the production line. Thus, there will be fewer returns and high customer satisfaction.

Retail Industry

The retail industry is undergoing a pivotal transformation with computer vision in retail. The primary application of computer vision in retail is in improving the self-checkout and cashier-less store experience. The computer vision systems can identify objects without the need for barcode scanning. With this, the turn-around time of the checkout process will decrease to a considerable extent, resulting in a smoother customer experience.

Computer vision has helped provide real-time inventory updates, optimize shelf management, and discover stock irregularities in inventory management. Simbe Robotics' robot, Tally, performs these tasks using computer vision.

Surveillance and Security

In surveillance and security, real-time analysis is a key aspect of computer vision. The application of computer vision technology in live video streams can help security personnel with real-time alerts in case of any anomalies or potential threats. This system is highly improvised over traditional surveillance methods, in which footage is often reviewed by humans only after a security incident has occurred.

In the surveillance industry, computer vision technology can reduce false alarms by up to 90%. Techniques like object detection enable computer vision to analyze surveillance camera footage intelligently.

Autonomous Vehicles and Transportation

Self-driving cars are the reality today. Companies like Tesla are leveraging various computer vision technologies to enable autonomous driving. They have built prototypes of navigating roads, interpreting signs, and avoiding obstacles. The computer vision AI can analyze driver video feeds in real-time to detect distraction, drowsiness, and impaired driving. This enables alerts that prevent fatigue-related accidents caused by human errors.

Furthermore, surround-view cameras, blind spot monitoring, lane keeping, and parking assistance increase safe driving.

Social Media and Entertainment

The entertainment industry's computer vision market is predicted to increase at a compound annual rate of 45.3% between 2020 and 2027. Computer vision automates image tagging and content moderation on social media networks by identifying problematic visual material.

On the other hand, there are various other applications, such as augmented reality, post-production video editing, and special effects. It can also provide immersive experiences like virtual try-ons and interactive gaming.

Furthermore, streaming platforms use computer vision to recommend personalized content per visual cues from previously watched content.

Healthcare

In the healthcare industry, computer vision technology can reduce costs by $150 billion by 2026 with 30% fewer medical errors. Most use cases are lying in processes like MRI, CT, and other medical scans to assist doctors in identifying tumors, fractures, pneumonia, and others.

Computer vision technology can detect abnormalities from medical images , provide clinical decision support, and enable earlier interventions.

Agriculture

In the agriculture industry, AI is keeping a close watch on livestock, performing automated quality operations, and keeping an eye on the structural health of infrastructure. There is a huge potential for computer vision in agriculture. It offers highly meticulous image analysis capabilities and improves how we monitor crops and predict yields. It can interpret the quality of the grown crops, growth patterns, and even potential stressors that affect crop yield.

Challenges and Future Perspectives of Computer Vision

Undoubtedly, there is an auspicious future for computer vision as it has many use cases across different industries. Furthermore, advancements in machine learning and artificial intelligence will drive better accuracy and efficiency in computer vision. It will lead to development of more sophisticated, reliable, and accurate computer vision solutions.

In the future, we also expect the increasing collaboration between human and computer vision systems in manufacturing, leading to greater efficiency and productivity. Finally, incorporating computer vision into ordinary consumer technology is expected to become more widespread, making our lives more convenient and efficient.

Wrapping Up

As we are leaping towards the future, computer vision technology will optimize operations in various fields like agriculture, ensuring product quality in manufacturing, improving stock management in retail, and paving the way for self-driving vehicles.

At A3Logics, the best AI development company, we have expertise in developing computer vision applications. Our team of developers has vast experience in developing cutting-edge solutions for different subsets of AI. Let us know your requirements.