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Computer Vision Advantages and Disadvantages


Artificial intelligence encompasses several different approaches to solving problems. Computer vision, object detection, natural language processing, and other types of artificial intelligence help businesses and individuals automate processes, improve accuracy, and work more efficiently. The subset of AI known as computer vision centers around visual processing and offers benefits in a range of applications. 

What Is Computer Vision?

Sight is a sense that the majority of humans take for granted. However, the processes required for physically seeing the world around you are quite complex. Think about all the things you do that require vision—walking, driving, reading, recognizing people, and so on. All of this requires a physical organ (the eye) that converts light into electrical signals, a neural network that carries those signals, and a mega processor (the brain) that allows us to perceive the world around us.

Computer vision is essentially the scientific attempt to replicate human vision in machines. The goal of computer vision, which is a field that is constantly evolving, is to teach computers to process images by recognizing patterns so that, ultimately, they can process images in the same way humans do.

How Does Computer Vision Work?

Whereas humans get image data by simply looking around, computers typically get it in a digital format from cameras that provide images and video. The image is converted to a matrix of pixels that is then stored in the computer’s memory and available for comparison to other images and patterns. Based on the images the computer has “seen” and the new images it processes, it can react according to the rules it has been given.

For example, a computer can learn that clusters of pixels with certain colors and shapes are cars. When it sees similar clusters in other images, it will recognize the object as a car. Just as humans learn how to recognize objects and faces, the longer a computer trains and the more images it learns, the better it is able to identify what it sees.

Examples of Computer Vision

This abstract definition may not seem familiar, but the fact is that people already interact with computer vision every day. Some of the most common applications include facial recognition, insurance claim assessment, Google image searches, and self-driving cars. If you’re a Facebook user, you’ve probably been prompted to tag yourself in a photo—that’s computer vision in action. Computer vision is also used in the healthcare industry to identify anomalies and provide more rapid diagnosis

Some other examples of computer vision in action include:

  • Quality control for manufacturing processes
  • Automated safety inspections
  • Quality assurance of product packaging and labels
  • Assessing image quality of user-generated content
  • Determining the efficacy of herbicides in agriculture
  • Identifying risky driving behaviors among fleets

The Advantages of Computer Vision

When it comes to computer vision, advantages are being discovered all the time as new applications are developed.

Improve Accuracy

One of the major advantages of computer vision is that it can be more accurate than human vision. The human brain is so amazing that it can complete images based on just a few pieces of information. It can sometimes also prevent us from seeing what is actually there. However, the complete picture isn’t always accurate because our brains make assumptions—try some optical illusions to see for yourself.

Computer vision reacts to images based only on the data that is presented—and, importantly, all of the data. Although it is able to make assumptions based on patterns, it does not have the disadvantage of a human brain’s tendency to leap to conclusions that may not be accurate. Computer vision also operates at the pixel level, which is a level of detail that the human brain does not process. This allows computers to provide more accurate results, which can be advantageous when it comes to applications such as using image-based detection for early cancer detection. 

Related: Download the checklist that lays out everything you should consider  before implementing a machine learning project or workflow →

Deliver Faster Results

The brain works fast and efficiently, but computers are better at multitasking, which can allow them to deliver faster results for some applications. Computers can also be dedicated to performing specific tasks for long periods of time. For example, tagging and categorizing a batch of 10,000 images for an e-commerce site might take a human six or more hours, not including time for breaks and the inevitable interruptions that happen in life. One example of this type of computer vision application is an online book retailer that uses image verification to automatically select the best thumbnails for product pages. 

Using computer vision to complete this task not only delivers results in a fraction of the time, but also frees up valuable time to focus on higher-level tasks that truly require human cognition. In a healthcare setting, using computer vision to process X-ray images enables faster diagnosis, which potentially leads to faster care at critical times. More recently, computer vision has been used to rapidly identify COVID-19 cases. 

Reduce Costs

Once a computer has been trained, it can repeat the same tasks with minimal cost—and even continues to learn while it does this. This can save countless hours of manual labor and the associated costs. One example is incorporating computer vision into surveillance systems to identify shrinkage in retail stores. Data from surveillance cameras can be used to identify gaps on store shelves, prompting retailers to keep popular items stocked and helping them identify purchasing trends.  

Whether the resources saved by using computer vision get allocated to people performing higher-level tasks or other expenses related to growing a business, this technology helps save money. Computer vision can also be used to recognize moods as people shop around a store and look at various products. Using this approach, stores can remove unpopular items to reduce inventory costs.

Provide Unbiased Results

When a computer looks at an image with a specific goal, the irrelevant information is not taken into account. This helps reduce the types of bias that humans might introduce to a process, whether intentionally or unintentionally.

For example, when an insurance adjuster looks at images of a damaged vehicle, they might become biased by the surrounding context, such as symbols of wealth, human expressions, and so on. However, when a computer analyzes the image, it looks only at the vehicle and the damage it sustained, providing an objective analysis of the insurance claim.

Offer a Unique Customer Experience

Computer vision has been used to enhance the customer experience both online and in retail stores. Online, it can be used to identify products or brands that an individual is most likely to buy based on images in social media profiles. In grocery stores, Amazon Go has used computer vision to revolutionize the shopping experience by detecting items in carts as people move throughout the space and automatically charge them, eliminating checkout lines. Facial recognition in retail stores also allows marketers to provide a customized experience from the moment customers walk in. 

The Disadvantages of Computer Vision

One of the most controversial aspects of computer vision is the potential for invasion of privacy. Facial recognition software is a particularly contentious issue, especially for people who are concerned about invasion of privacy through surveillance either online or in the real world. Many people consider having the ability to move freely or search the internet privately to be basic rights that computer vision could infringe upon.

By contrast, some argue that computer vision improves convenience and makes people feel more secure. Of course, there are trade-offs with any type of new technology, and the balance with computer vision continues to evolve.

To be effective, computer vision models must also be trained. This can be challenging if you don’t have an in-house data scientist or the right platform to guide you through the process. Fortunately, with, you don’t need to be a data scientist to create a computer vision model that meets your needs.   

Harness the Power of Computer Vision

When used ethically, computer vision’s advantages far outweigh its potential disadvantages. Whether you’re using it to improve your e-commerce website or to save lives through faster diagnosis, computer vision provides many benefits. Although it might seem like futuristic technology, the reality is that you probably interact with some form of computer vision every day.

If you’re curious about how you can employ computer vision in your organization to save time, improve accuracy, and reduce costs, try a pilot project to test it out. Our machine learning checklist is a great place to start, even if you’re new to AI and machine learning.