Modern cameras can capture visual information in high fidelity but taking pictures of objects is not the same as seeing those objects. Computer vision allows computers to extract valuable insight from images and videos. Right now, this technology is used in conjunction with machine learning and AI for facial recognition, traffic management, autonomous vehicle navigation, natural language processing, and more. 

Giving computers eyes is the next step in the development of AI which can give your business a strong boost. Today, we are going to discuss the ways it already changes industries and how you can benefit from this technology.

The benefits of computer vision

Computer vision has a wide range of uses across industries like supply chain and logistics, automotive, retail, and more. As much as we use our eyes to see and understand the world around us, so do the computers to analyze and interpret visual data. This allows you to process and use the data faster and easier, and that is just one of many benefits of this technology.

Human vision vs computer vision

Process data in a simpler and faster way

Computer vision systems can perform repetitive tasks faster and more efficiently than humans. For instance, this technology can make the use of surveillance cameras much simpler: in case anything suspicious appears at sight, the computer vision system will alert your security department for further actions to be taken. You would not need a human employee sitting at the security desk checking screens for hours on end.

Reduce costs

Computer vision can help in identifying flaws in your product and alert you to any issues. You can give the computer a sample image of a particular product, and the system will compare it to other products of the same design you make and trace any deviations from the sample. This will help you fix the issues before they snowball into larger problems. These systems will also eliminate obsolete human labor allowing you to allocate your resources more effectively. 

Natural language processing 

As a part of the Artificial Intelligence domain, CV is intertwined with the concept of Natural Language Processing too. Computers can now read the written or typed text. This can be used for processing contracts and finding any errors or inconsistencies in the written text. 

Biometrics authentication

This is especially relevant for facial recognition technology. Not only does the computer recognize human faces in general, it can also recognize the unique faces of particular individuals. Take facial recognition phone lock systems: your phone knows your face and can distinguish you from any other person. 

Facial recognition is one of the better known computer vision advantages that does not just protect your phone; it can also be used in retail, banking, transportation, and other industries as a security measure. Your face is a primary visual identifier by which you get recognized by other people, and now, computers too can recognize your face to give you access to your private and sensitive data.


Image processing has proven vital for the identification of abnormalities in organ scans in clinical environments. Doctors can use computer vision advantages in different situations, including for cancer identification. This can help the physicians to process the collected patient data much faster and give more precise diagnoses.

Additionally, the AI can help in identifying the amount of blood loss in women after giving birth. With the new tech, the doctors can adjust treatment in accordance with each particular patient’s condition and prescribe relevant treatment. The use of computer vision will soon expand to other areas enhancing the quality of care and life expectancy of the patients. 

Deepfake detection

With fake news taking over the media space, it becomes harder for the average person to determine what’s real and what’s not. Deepfakes are becoming so good, even the experts might fail to identify them. The system can identify the elements of photos and videos that have been manipulated in any way. 

Autonomous vehicles

Computer vision is being used extensively in the production of autonomous vehicles. This technology helps the vehicles to identify obstacles on the roads, see other cars, pedestrians, and other objects to avoid collisions. We will be seeing more and more autonomous vehicles on the streets in the following years and flawless performance of these systems will become a critical component of traffic safety. 

Law enforcement and defense

Technology can be extremely helpful in ensuring public security. Of course, there’s a controversy surrounding public surveillance, but the fact remains that this technology can help detect suspicious individuals, dangerous criminals, and terrorists in public places. The technology can also be used in defense, helping the military identify weapons of mass destruction and other hazardous objects over vast areas.

Challenges to a proper adoption of new tech

Incomplete data sets – computers are still struggling to process incomplete visual data. While humans can fill the blanks based on our experiences and logical assumptions, computers have not reached quite that level of intelligence just yet. That is why you will have to train your computer vision system to do that. 

Failure to process images – there are lots of factors that can throw your system off. Shades, coloration, darkness and light, odd shapes – all of that may confuse the system causing it to fail. Though a well-trained system can deal with most of those issues, it might still fail to process something it did not encounter before.

Trained specialists required – a company trying to adopt this new technology will need a team of experts in AI and Machine Learning to train the system. The technology is in its early stage and the systems require supervision to function properly.  

All the current computer vision advantages and disadvantages can be used or dealt with if you have a team of qualified experts at your side. The race for the best engineers is real, and the best course of action is to partner with a software development company that will help you pick the right tech stack and deliver the solution you need.

How a proper technology partner solves your challenges

Choosing a reliable partner who can get your project from the discovery phase and up to the market launch is paramount. An experienced software development partner will map out the entire development process, estimate TCO and ROI, collect all the project artifacts, produce necessary deliverables, and transition into the implementation phase. 

Machine learning in computer vision

Proper implementation of the computer vision system requires a strong team of experts to collect and compile the necessary data. They will also have to teach the system to correctly recognize the images and identify objects. This will include several steps.

Improve source and training data

For the effective analysis of the visual information, you will need a sufficient amount of reliable data. The developers will create the necessary data sets for the training model, which will result in more accurate image recognition.

Data augmentation is a critical part of this process as it allows you to greatly increase the diversity of data sets without actually collecting the data. The techniques may vary depending on the type of visual data and the complexity of the application.

Incremental learning allows you to improve your computer vision system without processing large amounts of data at once. In this case, machine learning starts with a very simple model and gradually progresses to more complex models with higher degrees of deviation. 

Reinforcement learning will help the system build up the experience through positive and negative feedback from the human expert. Basically, the system will receive positive signals for accurate recognitions and negative signals when making false recognitions. This is a machine learning approach that helps the system learn from its successes and failures. 

Increase training and testing of models

Testing and training the models on properly annotated images and videos with clearly defined metadata is critical for building an effective and error-free computer vision system. In most cases, we select 20% of data sets for testing and the remaining 80% for training. The training set teaches the model to recognize images and predict target values. The remaining data sets are used for testing the quality of learning and finding whether the model is good at making predictions beyond the learning data. 

Of course, to make it all come together into a fully functional system, you will require a team of experts. And that is exactly what N-iX does – we give you dedicated teams of experts who will apply relevant machine learning models to make your system work as intended. Introducing new systems into your business operations is a challenging process but many companies have already seen substantial growth by establishing partnership bonds with reliable development companies.

Computer vision solution for a German Fortune 100 company

We helped a German engineering and technology company to improve the logistics between its 400+ warehouses. As a software development partner, the N-iX team had to come up with a set of solutions to help the client change the architecture of the current system and introduce necessary improvements.

Among several solutions we came up with, there was a need to redevelop the existing CV algorithms due to their inefficiency. We’ve examined the existing computer vision solution and decided to change its architecture by introducing a Continuous Delivery for Machine Learning. This solution allowed us to implement continuously repeatable cycles of training, testing, deploying, monitoring, and operating the ML models. 

The client also needed a multiplatform mobile application, and our team designed an architecture for it and developed the CV mobile app. The application has such features as object detection, product damage detection, OCR, and NLP for document processing. 

Improving traffic management efficiency

We’ve leveraged a number of computer vision advantages to develop a solution for an Australian company that creates intelligent transport solutions for government, police, and traffic departments. The company’s main focus is to reduce emissions, minimize traffic jams, eliminate fatal crashes, and make our roads safer for both drivers and pedestrians. 

The client needed a software development partner who’d be able to develop a computer vision system for an intelligent transport solution. Together with our client, we’ve worked on such tasks as windshield detection, person detection, and seat-best classification. 

We’ve created a computer vision system that detects whether the driver has fastened the seat-best or not. It can also identify the drivers engaged in distracting behaviors such as texting or talking on the phone, eating, drinking, etc. The system has an automatic Number Plate Recognition and AI recognition of vehicles. It allows for identification of the offenders and fines filing based on captured data.

Final Thoughts

Computer vision is a technology that has the potential to change most industry verticals within the current decade. Keeping the computer vision advantages and disadvantages in mind, you can develop a solution that matches your unique business needs. Making computers see and understand what they see is a huge leap for the AI domain and all the industries that rely on the timely development of AI as a whole. 

If you want to use this technology to improve your business and maximize its efficiency, you will need a reliable partner who has sufficient expertise in that domain. N-iX team offers expertise in Data Science, AI, Machine Learning, and CV to help you achieve a new level of business efficiency.