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Top 8 Computer Vision Use Cases and Examples in 2024

Computer vision (CV) refers to replicating the human visual ability in a computer or machine. Computer vision technology is being intensively used in many sectors, including retail, agriculture, manufacturing, etc. The global computer vision market is projected to surpass $41 billion by 2030 (See Figure 1).

Figure 1. Computer vision market growth by component 2020 & 2030.

Source: Allied market research

As investments in computer vision rise, business leaders must learn more about the technology and how it can be implemented in their business.

This article explores the top 8 use cases of computer vision in different industries and examples.


In the past, doctors spent hours analyzing medical data to identify diseases and make diagnoses. As the number of patients and the demand increases, speed is something the healthcare sector needs. Now medical data analysis has become faster and more accurate through computer vision technology.

Medical image analysis

A computer vision-based system can accurately analyze x-rays, CT scans, MRIs, and other medical images to identify abnormalities such as tumors, blood clots, etc., that are not visible to the human eye. Since there is currently a shortage of radiologists in the market, computer vision can be a way to overcome this issue.

Cancer Detection

A computer vision system can also detect skin cancers by analyzing images of skin abnormalities. Similarly, computer vision and AI-enabled systems can accurately analyze mammograms for breast cancer detection.

To learn more, check out our article on computer vision use cases in the healthcare sector.

You can check our list of medical data annotation tools to find the option that best suit your CV project needs.


The global computer vision market in the manufacturing sector is growing as more businesses understand the benefits of the technology. Here are some use cases:

Quality control

Quality control is one of the most common applications of CV in manufacturing. Since it is a repetitive and error-prone task, manual quality control processes are inefficient when implemented in large-scale factories. Computer vision QA systems can work with much higher speed and accuracy and save manufacturing facilities time and money.

This is how it works:

Facility automation

Computer vision is also used in automating different functions such as assembly of product parts and worker safety monitoring in a manufacturing facility.

Many production facilities in the automotive industry use computer vision-enabled assembly bots to assemble products with higher speed and accuracy.

See how BMW uses computer vision and AI to detect car models on its assembly line:

To learn more about computer vision use cases in the manufacturing sector, check out this quick read.


New innovations in the retail sector, such as cashier-less stores and smart surveillance systems, are all enabled by computer vision. Here is how:

Cashier-less stores

During the global pandemic, retail stores became high-risk areas for customers and employees. Computer vision and artificial intelligence allow automation in retail stores and can help overcome these risks. 

After the initial launch of Amazon’s cashier-less convenience stores Amazon Go, many other businesses, such as San Jose University, adopted this idea by implementing computer vision-enabled systems in their convenience stores.

Smart stores surveillance

Monitoring shelves and customers at retail stores can be a tedious task if done manually. Computer vision-enabled cameras can:

  • Monitor store shelves
  • Monitor each product on the shelves
  • Examine inventory levels and alert for replenishment
  • Monitor customer movements in the store to identify hot spots
  • Analyze customers for potential shoplifting and theft

To learn more about computer vision in the retail sector, check out our comprehensive article.


Computer vision technology is revolutionizing the transportation industry. Here are some use cases:

Autonomous vehicles

The global autonomous vehicle market is projected to reach $62 billion by 2026. Computer vision is the core technology that allows autonomous vehicles to work.

Figure 2. A simple computer vision self-driving car system

Source: Medium

Self-driving vehicles are also being used to automate the logistics sector to increase efficiency and reduce lead times in road logistics. 

See how self-driving trucks could eliminate the driver shortage issue in the logistics industry.

Road traffic analysis

Computer vision systems are also used to analyze traffic conditions through cameras mounted on roads. The data from the computer vision system can be input into urban traffic management systems to help optimize traffic flow in the city.

The German city Darmstadt uses a computer vision-enabled traffic management system to improve its traffic flow.

Further reading

You can also read:

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Cem Dilmegani
Principal Analyst
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Shehmir Javaid
Shehmir Javaid is an industry analyst in AIMultiple. He has a background in logistics and supply chain technology research. He completed his MSc in logistics and operations management and Bachelor's in international business administration From Cardiff University UK.

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