Machine and Computer Vision: Definition and Technology


Machine and computer vision are two technologies that are closely related. Do they have a difference? We’ll talk about this a little lower. Machine and computer vision have recently become widely used in industry and production. And all because in some tasks, robotic machines are much more practical, faster, more accurate and cheaper than people. And most importantly, they are able to work 24 hours a day.

What is the difference between computer vision and machine vision

Although in some cases these terms are not separated from each other, they still have slight differences depending on the context in which they are used. But at the same time, there are adherents of the fact that these two terms are one and the same. Therefore, it will not work to find a single and exact definition of the difference, you can only listen to the majority. And the majority thinks the following :

Computer vision is a separate area in artificial intelligence. It covers only the theory and technologies that are applied to recognize objects and makedecisionsabout these objects. Most often, this combination of words is used when describinghowcomputers simply “see” the environment.

Machine vision is the most practical application of computer vision. This combination of words is most often used when describing the use of computer vision in manufacturing equipment and in industry to improve the work process. This concept already includes: the work of “computer vision” + the ability to recognize visible images + the ability to analyze visible images + decision-making based on image analysis.

For an ordinary person, the difference between these terms is unlikely to be noticeable. Therefore, in this article it makes sense to combine these two values ​​​​together and figure out how it all works.

Tasks performed by machine vision

Machine vision in industry and production can perform the following tasks:

  1. Recognize. The classic of computer vision is to recognize objects using video cameras. Machine vision is the use of this “recognition” to analyze visible objects for features, properties, differences from other objects, characteristics, etc.
  2. To identify. The object is identified individually. For example: people’s faces, fingerprints, car tire tracks, etc. are identified.
  3. Find. The received video data is analyzed and the desired object contained in the database is detected. Example: Find a criminal using the Safe City video camera system.
  4. Recognize text. The received video data is analyzed for the content of certain characters. Or, characters of printed and even handwritten text can be recognized on the image.
  5. Assess movement. A typical example is tracking the movement of objects (cars, people, etc.).
  6. Restore images and videos. Provided that part of the scene is present, the image or video scene can be restored completely.
  7. Segment. It is used to search for the desired objects among many other similar ones.

This cannot be a complete list of tasks, as machine and computer vision is constantly updated with scope. More and more new areas where machine vision technology is applied appear almost every day, because “machines” learn and new opportunities open up. Why it happens?

According to DZOptics, people have noticed that machine vision is absolute accuracy in calculations and lightning-fast reaction when analyzing and making the right decisions. Machines in “observation” never rest, miss nothing and are not distracted. And the introduction of neural networks into this technology gave a tremendous impetus and unlimited possibilities, if necessary, to detect and recognize an object: whether it is a part on a conveyor belt at a factory or a person’s face in a crowd, it doesn’t matter to machine vision.

Where is machine and computer vision used?

We all saw when machine and computer vision is used in production, industry or everyday life, we just did not pay attention to it at that time. A few main areas where you can see this technology:

  1. Video surveillance in the office, production, on the street, in the supermarket.
  2. Autopilots in self-driving cars use machine vision to avoid obstacles.
  3. In medicine, systems for analyzing various images.
  4. Machine vision in industry for sorting and searching for defective parts.
  5. VR and augmented reality technology.
  6. In construction to control the quality and accuracy of structures.
  7. Reading a barcode from goods in a supermarket.
  8. Face ID in smartphones.

Every day we are faced with machine vision, not realizing that this is it. And how many spheres are still hidden from ordinary human eyes?

It happens like this:

  1. Video cameras in the hall record the movement of customers.
  2. The data is sent to the server for analysis.
  3. After analyzing the video data, a “heat map” of the movement of customers is compiled.
  4. Where the most “hot” spots are observed, they lay out goods that need to be sold faster or that bring more money.

And that is not all. Machine vision analyzes the state of roads for traffic jams, analyzes satellite maps for the presence of infrastructure facilities and the need for them depending on the place of residence and movement of people.

In general, machine vision is already part of our modern life, and there is no getting away from it.

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By aamritri

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