Industrial image processing

July 12, 2021, 6:21 a.m.

Image processing is one of the most widely used parts of machine learning and artificial intelligence.

In the previous articles of the site, we wrote about the industrial solutions based on ai and machine learning in manufacturing, in the continuation of this article, we intend to discuss the uses of image processing in the industry;

What is image processing?

Image processing is a way to perform some operations on an image in order to obtain an improved image or extract useful information from it.

In other words, image processing is a type of signal processing in which the input is an image and may be the output of the image or the features associated with that image.

These extracted features can be used to identify objects, categorize photos and other items related to machine vision.

Uses of image processing in industries

There are many applications and uses of image processing in various industries, the following are some examples of these:

For example, in manufacturing, machine vision is used to detect, count, and measure to help automate the process.

Also used in military and security, computer image and vision processing for target detection, tracking, object detection, and more.

Or used in the photography and film industry, image processing to enhance images, cleaning, cropping, blending, etc.;

Image processing in smart manufacturing

Visual inspection and quality control of manufactured products is usually performed by humans. Although people are very good at this and even better than machines, they are much slower and can not work for long.

In many factories, information must be quickly and repetitively extracted, processed and decided to increase the production process.

That is why advances in image processing technology have led to new booms in productivity and quality in most industrial applications.

For example, inspecting certain environments in the aerospace or construction industries can be dangerous or difficult. Machine vision can be a good alternative to human inspection.

Industrial image processing on production lines

Industrial image processing allows instant and automatic monitoring during the production process. Also, high-speed production lines, industrial image processing are able to accurately record and identify faulty items.

Cameras with image processing capability can be used in places where there is no access for people to monitor, such as areas where the temperature is very high or in polluted environments.

Industrial image processing is mostly based on the use of camcorders installed on the production line and a highly efficient computer for image processing.

For industrial image processing, resolution is not just a matter of pixels. Pixel size and form, as well as image sensitivity and size, and the ability to control the exposure and the camera's ability to perform partial scans are important;

For example, in a factory, defective parts must be identified, this can be done using image processing.

Industrial inspection process steps

1. Putting the camera in the right place to capture images, in vision everything depends on the image. Any initial defects in the images can have serious effects on image analysis and interpretation.

2- Collecting and processing the images that have been recorded

3- Division of recorded images

4- Feature extraction: Feature extraction is done to reduce dimensions. This includes reducing the amount of information needed to accurately describe a large set of data. Examples of features include size, position, contour measurement, and texture recognition. These properties can be extracted using statistical, structural, block matching, neural or fuzzy networks. The calculated feature set forms the description of the input image

5- Decision making: The system must decide whether the production result is in accordance with the quality standards and calculated characteristics or not, which makes this comparison according to the data already given to the system.

What industries use image processing?

Today, the use of machine vision technology and image processing techniques and due to the economic justification of this system has been widely used in the industry in the long run and its growth trend has been significant in most projects.

These projects use image processing in counting and measuring objects, object classification, dimensional measurement and calibration control, fault detection including crack detection, label inspection and reading of barcodes and characters on the product and many other operations. The use of vision machines encompasses a wide range of applications, including their use in the following industries:

  • Pharmaceutical and medical equipment industries
  • Automotive industry
  • Packaging Industry
  • Tile and stone industry
  • Plastic and polymer industry
  • Pipe and cable industry
  • Food and beverage industry
  • steel industry
  • Agriculture industry
  • Parts industry
  • Boards and electrical equipment production lines, including mobile production lines
  • cosmetics
  • Control of industrial machines (industrial robots and mechanical arms)
  • Nuclear and aerospace

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mahdiyeh parastar

I have a bachelor's degree in robotics engineering and a master's degree in mechanical engineering. I work in deep learning networks and classical networks

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