Analytics, AI/ML

27 Use Cases Of Computer Vision Application

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27 Use Cases Of Computer Vision Application

Ever wondered how computers can "see" and interpret images just like humans do? This is where computer vision comes in. Computer vision is a field of artificial intelligence that allows machines to analyze and interpret visual data from the world around us. This technology has numerous real-world applications across different industries. In this article, we will explore 27 use cases of computer vision applications across six categories:

  1. Transportation
  2. Healthcare
  3. Manufacturing
  4. Construction
  5. Agriculture, and
  6. Retail

So, let's dive into the world of computer vision and see how it is revolutionizing the way we live and work.


In the past few years, technology has transformed transportation industry. Computer vision has become a game-changing technology in this field, changing how we get around and how we get to work. Let's take a look at some of the most common uses of computer vision in transportation.

1. Self-driving cars

Self-driving cars are one of the most exciting and far-out ways that computer vision is used in transportation. Technology is no longer just a dream. Thousands of engineers and developers around the world are already testing and improving the safety and reliability of self-driving cars. A report by Allied Market Research says that the market for self-driving cars will grow at a CAGR of 40.1% from 2021 to 2030, taking it to $2161.79 billion by 2030. Computer vision is a key part of making self-driving cars a reality because it helps them find their way around, recognize traffic lights and signs, and spot obstacles in real-time.

2. Pedestrian detection

Pedestrian protection systems and smart cities need the ability to find and keep track of people walking. Pedestrian detection algorithms that use computer vision can find and follow people in real-time, alerting drivers to their presence and possibly preventing accidents. According to a report by the National Highway Traffic Safety Administration (NHTSA), 6,283 pedestrians were killed in traffic crashes in the United States in 2018. Pedestrian detection using computer vision technology can significantly reduce this number.

3. Parking occupancy detection

In Parking Guidance and Information (PGI) systems, computer vision is often used to see if a parking lot is full. These systems tell drivers in real-time where parking spaces are available, which makes parking a lot easier. According to a report by MarketsandMarkets, the parking management market is expected to grow from USD 3.8 billion in 2020 to USD 5.4 billion by 2025, at a CAGR of 7.4% during the forecast period. This growth is likely to be helped a lot by computer vision-based parking occupancy detection.

4. Traffic flow analysis

With the help of computer vision technology, drones, and cameras can now be used to track and estimate how much traffic is moving. This is important for transportation planning because it lets officials look at traffic patterns, find bottlenecks and congestion, and make decisions based on data to make traffic flow better. According to a report by ResearchAndMarkets, the global traffic management market is expected to grow from 38.2 billion in 2022 to USD 68.8 billion by 2027, at a compound annual growth rate (CAGR) of 12.5%

5. Road condition monitoring

Using changes in concrete and asphalt, computer vision can be used to figure out how good the infrastructure is. With computer vision-based algorithms, it is possible to find cracks, potholes, and other problems in the road surface. This can help authorities decide which maintenance and repairs to do first, making the roads safer for drivers.

Computer vision-based road condition monitoring systems can do more than just find cracks and potholes. They can also help find problems like uneven road surfaces and fading road markings. By analyzing the visual data collected from cameras on vehicles, drones, or even roadside poles, these systems can give real-time information about road conditions, allowing authorities to take action as needed.

Also, with the help of machine learning, computer vision systems can use current data to predict how roads will be in the future. This lets maintenance and repairs be done before any major damage happens.


Computer vision is changing healthcare because it helps doctors make more accurate diagnoses, improves patient outcomes, and speeds up the process. Here are some of the best ways that computer vision could be used in healthcare.

6. Diabetic retinopathy screening

Diabetes-related damage to the retina is a leading cause of blindness around the world. Most cases of blindness can be stopped if they are found early and treated. Algorithms for computer vision can look at pictures of the retina to find diabetic retinopathy. A study from the National Library of Medicine found that a deep learning algorithm had an accuracy rate of 90.3% in detecting diabetic retinopathy, which was higher than that of ophthalmologists.

7. Skin cancer detection

The most common type of cancer is skin cancer, which is found in about 9,500 people every day around the world. Early detection is very important for treatment to work. Skin cancer can be found by using computer vision algorithms to look at pictures of skin lesions.  A study published in the Annals of Oncology found that a deep learning algorithm had an accuracy rate of 95% in detecting skin cancer.

8. Surgical assistance

Surgeons can also use computer vision to help them do their jobs. Computer vision algorithms can look at images from cameras on surgical tools to help surgeons find structures in the body and guide them through complicated procedures. This technology has shown a lot of promise for making surgeries go better and lowering the chance of problems.

For instance, in laparoscopic surgery, where a small camera is inserted through a small incision to give a view of the surgical site, computer vision can be used to improve the quality of the images and make the procedure significantly more accurate.

By looking at live video feeds from surgical cameras, computer vision can also help find potential problems during surgery, such as bleeding. This lets surgeons make better decisions in real-time, which lowers the risk of complications and makes things better for the patient.

9. X-ray analysis

X-rays are often used to diagnose a wide range of medical conditions, but even for experienced doctors, it can be hard to figure out what the images convey. Computer vision technology can help interpret X-ray images, which could make diagnoses more accurate and cut down on the time it takes to look at images.

For example, a study that was just published in the journal European Society of Radiology showed that an AI model trained on X-ray images could find wrist fractures better than human radiologists. The model achieved an accuracy rate of 96% compared to the radiologists' accuracy rate of 79%.


The improvements in computer vision have made a big difference in the field of manufacturing. Using computer vision in manufacturing has made factories more accurate and efficient, cut costs, and made them safer. Let's look at some of the best ways that computer vision is used in manufacturing.

10. Quality control

The way quality control is done in the manufacturing industry has changed a lot because of computer vision. It has made it possible to find problems in products with a very high level of accuracy. For instance, computer vision is used in the auto industry to find problems like scratches, dents, and parts that aren't lined up right. Using computer vision to check for quality has not only cut down on production costs but also made customers happier.

11. Robotic guidance

Computer vision is a big part of how robots are guided. Robots are used more and more in manufacturing to do things like welding, putting things together, and painting. Robots can do these tasks accurately and quickly with the help of computer vision. Using computer vision, manufacturers can cut the time it takes to make a product by a large amount, boost productivity, and cut costs.

Computer vision can also improve the quality of the things that robots make. By looking at pictures of the product and its parts, computer vision algorithms can make sure that each part is put together correctly and that no parts are broken or missing. This can greatly cut down on the number of bad products and make the whole manufacturing process better.

12. Predictive maintenance

In manufacturing, computer vision is also used for predictive maintenance. With predictive maintenance, data, and analytics are used to figure out when a machine is likely to break down. Computer vision is used to keep an eye on machines and find problems with how they work. By finding these oddities early, manufacturers can fix the machines before they break down, cutting costs and downtime.

13. Inventory management

In manufacturing, computer vision is also used to keep track of inventory and manage it. It lets manufacturers keep accurate track of inventory levels, spot stockouts, and find the best levels of inventory. Using computer vision to read barcodes and analyze a product faster and more accurate than manually. Computer vision can also help organizations manage inventory, thus helping them work more efficiently while simultaneously cutting down on costs.

Computer vision can also help manufacturers improve the layout and use of space in their warehouses. Using computer vision algorithms, manufacturers can look at how people move through the warehouse and find the most popular spots. This information can be used to improve how products are stored in the warehouse making them easier to retrieve when needed, thus increasing overall efficiency.

14. X-ray inspection

Computer vision is also used in the manufacturing process for X-ray inspection. It is used to check things like food, medical devices, and electronic parts. Computer vision makes X-ray inspections faster and more accurate than older methods. This means that inspections don't have to be done by hand as often, leading to more efficiency, lower costs, and better-quality products.

X-ray inspections that use computer vision can also find flaws that can't be seen with the naked eye. This includes things like cracks, holes, and foreign particles that are on the inside of the product and can affect how safe and reliable it is. With the help of computer vision, manufacturers can find these flaws early on in the manufacturing process, making it less likely that a product will fail or need to be taken back.


Computer vision and AI have also been used in the construction industry to improve efficiency, cut down on mistakes, and keep workers safer. Here are some examples of use:

15. Defect detection

Computer vision can find flaws and other problems in building materials like concrete, steel, and wood. By looking at pictures or videos of building materials, computer vision algorithms can find cracks, corrosion, and other problems that could make buildings unsafe. In fact, a study from the University of Seoul showed that computer vision-based inspection systems can find up to 97% of defects in concrete surfaces.

16. Site monitoring and safety

Computer vision can be used to keep an eye on construction sites and make sure they follow safety rules. For instance, computer vision algorithms can find workers who aren't wearing safety gear, find trip hazards, and find equipment that is being used dangerously. By keeping an eye on sites in real time, project managers can quickly find safety risks and take steps to fix them.

17. Resource optimization

Computer vision can also help construction projects make the best use of their resources. For instance, computer vision can be used to track the movement of workers and equipment on construction sites. This can help find places where resources aren't being used as well as they could be. By looking at how their resources are used, construction companies can find ways to be more productive and save money.

18. Prefabrication

Prefabrication is becoming more popular in the construction industry, and computer vision is a big reason why. By using computer vision to look at design data and make 3D models of building parts, prefabrication companies can make parts with more accuracy and speed.

This can cut down on mistakes, make the product better, and speed up the process of making it. Also, computer vision algorithms can be used to check the quality of the finished parts before they are sent to the construction site. Computer vision can also help find problems and improve the quality of the building project as a whole. Moreover, using computer vision for prefabrication can save a lot of time and money while simultaneously improving the quality and speed of the building process.

19. Progress tracking

Computer vision can also be used to keep track of how building projects are going. By looking at pictures and videos of construction sites, computer vision algorithms can find completed tasks, track the movement of materials and equipment, and give real-time updates on project timelines. This can help project managers find possible delays and fix them before they affect the project's schedule.


The field of agriculture has found many ways to use computer vision. Here are some ways that computer vision is used in agriculture, from crop monitoring to plant health analysis:

20. Crop monitoring

Computer vision can be used to keep an eye on crops and notice changes in how they grow. This lets farmers make better decisions about how to take care of their crops. For example, they can find parts of the crop that aren't growing as well as others, possibly because of problems with the soil or watering, and fix them. This can lead to better use of resources and more crops per acre.

21. Plant health analysis

The health of plants can also be checked with computer vision. Computer vision algorithms can find signs of stress or disease in plants by looking at pictures of them. This lets farmers fix the problem before it spreads to other plants or crops. A farmer, for example, can use computer vision to look at the color and texture of plant leaves to see if they are getting enough water and nutrients.

22. Precision farming

Precision farming uses technology to put fertilizer, water, or other inputs in only certain parts of a field, instead of spreading them out evenly. Based on things like soil quality and how plants grow, computer vision can help figure out which parts of a field need these inputs, thereby enabling better usage of resources thus leading to better crop yields.

It can also find plant diseases, pests, and weeds and keep track of them. By looking at pictures of plants, computer vision algorithms can find signs of disease or pest infestation before people can see them. This lets farmers act quickly to stop the spread of diseases and pests, which ultimately leads to healthier crops and higher yields. Computer vision can also be used to ascertain when to harvest crops. It can look at pictures of plant and figure out the best time to harvest based on things like how mature they are and what color they are.

23. Robotic farming

Robotic farming could change the agriculture industry in a big way. With computer vision technology, farmers can finish activities like planting, watering, and harvesting crops without having to do them by hand. This can greatly improve efficiency and cut down on the cost of labor.

For instance, using computer vision in precision agriculture can help farmers use fewer pesticides and fertilizers while getting the most crops out of their land. Computer vision can be used to find plants that need water or nutrients and give them exactly what they need.

Also, robotic farming can help the agriculture industry deal with the problem of not having enough workers. With the help of computer vision and robotics, tasks that would normally need a person's help can be done automatically. This makes farming an easier and more appealing job for younger generations to get into.


Using computer vision in retail has changed how people shop and helped retailers improve how they run their businesses. Here are a few of the most common ways that computer vision is used in retail:

24. Smart shelves

Smart shelves with computer vision use cameras and sensors to track and analyze how products move on the shelf. This helps retailers keep track of their stock and know when they need to restock. This technology helps retailers lower their inventory costs, improve their supply chain management, and make customers happier by making sure they always have the products they want in stock. For example, Kroger, the biggest grocery store chain in the U.S., has put smart shelves in all of its stores, which has led to a 20% rise in sales.

25. Self-checkout systems

Self-checkout systems that use computer vision let customers scan their items and pay for them without the help of a cashier. This technology speeds up the checkout process and saves stores money on labor costs. A report from NCR Corporation, a company that makes retail technology solutions, says that self-checkout systems can speed up transactions by up to 40%, which makes customers happier.

26. Customer analytics

Customer analytics tools that use computer vision look at how customers act in a store, such as how long they stay, how they move around, and what they buy. This information helps retailers learn more about their customers and make decisions based on the facts to improve their business. For example, Walmart uses computer vision to watch checkout lines and make sure customers don't have to wait in line for too long. This makes customers happier and keeps them coming back.

27. Visual search

Visual search technology uses computer vision to identify products based on their pictures. This lets customers search for products by taking or uploading a picture. This technology makes it easier for customers to find products and helps retailers sell more by suggesting similar products based on what the customer is looking for. For instance, ASOS, a British online clothing store, uses visual search technology that lets customers find products that are similar to the ones they like by just uploading a photo.


As we can see, computer vision technology can be used in a lot of different fields. This includes the transportation, health care, manufacturing, building, farming, and retail industries. With the availability of more high-quality image data, and machine learning algorithms getting better by the day, we can expect to see even more creative uses of this technology in the future.

Ultimately, by using the power of computer vision, businesses can gain insights, automate tasks, and improve efficiency, which can lead to better products and services for customers. As technology keeps getting better, it will be interesting to see what new uses come up and how they change our world.

If you're interested in learning more about how computer vision can benefit your business, Cogent Infotech offers a range of services to help you stay ahead of the curve. Check out our website for more information.

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