Technologies that can recognize faces and objects are developing. According to the research of the Insight Partners, the market of machine vision systems will reach $14.48 billion by 2025.

Let’s find out what machine vision is, how the technology works with AI, and what industries are already using it.

What is computer and machine vision?

It is important to understand that machine and computer vision are overlapping notions that have differences.

Computer vision is the technology that allows machines to find and recognize objects as well as track and classify them.

Thus, using computer vision, machines identify objects, process video analytics, describe images, recognize gestures, and process results.

Machine vision is the use of computer vision for industrial purposes. Computer vision includes a general set of technologies, whereas machine vision uses the analysis of images to solve industrial tasks.

AI in machine vision

Thanks to the fact that modern processors have high computation capacity and big data is rather simple to use, machine vision deploys artificial intelligence.

The technology helps computers to advance from their own experience using deep learning. Itdiffersfromtraditionalapproachesappliedinmachinevision.

For example, AI analyzes images that standard programs cannot characterize accurately and unambiguously. Thus, artificial intelligence allows the technology to find industrial use.

Components and tasks of machine vision

The system of machine vision comprises a variety of components. As a rule, it consists of digital cameras that obtain images and smart cameras that process data.

Besides, the system includes a computer with a high-power processor, AI software, input-output equipment, light sources, and timing sensors.

Main tasks solved by machine vision are:

• recognition of objects and text;
• face identification;
• detection;
• reconstruction of shape basing on images;
• movement estimation;
• reconstruction of things shown in the image.

The technology solves many tasks in different areas:

• medicine – helps to diagnose diseases;
• manufacturing – uses robots in production;
• car industry – is responsible for the navigation of autonomous vehicles;
• retail – counts customers and recognizes bar codes.

In such a way, machine vision allows automating manual labor speeding up workflow at companies.

Where machine vision is already used

Machine vision in China

Today China has the world’s largest network of 200 million surveillance cameras. Moreover, ATMs authenticate customers using the face recognition technology and PIN codes.

Besides, face recognition technology is used in one of the Chinese schools, where AI tracks attentiveness of pupils. The system recognizes 7 different facial expressions and defines how well pupils focus on the lesson.

Police officers use smart glasses in Zhengzhou. With machine vision and face recognition technology, the device helps law-enforcement agencies to catch lawbreakers.

Sberbank’s face identification system

In January of 2019, Sberbank announced plans to launch a pilot project that would use face recognition for customer identification.

Sberbank’s reps state that the experiment will be carried out in several offices and the more often a specific customer will be approaching the camera, the more accurate will be the operation of the system.

According to Sberbank’s data, such a technology will be also used for employees, and some departments are already using face recognition access systems.

Disease detection

Machine vision is widely used in medicine. For example, Israeli firm Aidoc uses AI and image recognition technology to increase performance efficiency of roentgenologists.

Aidoc detects intracerebral bleedings using CT scans – the technology analyzes images and makes the diagnosis.

Moreover, machine vision helps to diagnose diabetes. IDx is one of the companies that develops solutions intended to detect diabetic retinitis. The system interprets images of retina and makes the diagnosis on its own.

Experts will discuss machine vision and artificial intelligence technologies at AI Conference Kyiv.

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