Machine vision is a system that operates equipment based on image capture and processing. According to the Automated Imaging Association (AIA), it includes all industrial and non-industrial applications that combine hardware and software. Many of the algorithms and approaches used in industrial computer vision are the same as those in computer vision applications such as research, educational, political, and military applications, but with different constraints.
Industrial vision systems are required to have higher robustness, reliability, and stability than vision systems for research and educational purposes. On the other hand, it is cheaper than those used for political and military purposes. This means that industrial machine vision is low cost, has acceptable accuracy, is robust, reliable, durable and temperature stable.
Machine vision systems utilize a protected digital sensor inside an industrial camera equipped with a special optical system to capture images. Computer hardware and software process and analyze these characteristics to produce measurement results.
Example of filling level inspection system
Consider, for example, the filling level inspection system used in breweries.
Example of bottle filling level inspection. There are only two types of reactions, pass or fail. This is a characteristic of binary systems..
When the beer bottle passes the inspection sensor, the vision system starts activated. Besides, the strobe starts struck, and the bottle starts photographed. The picture taken starts stored in memory as an image, after which vision software processes or analyzes the image and determines pass / fail according to the filling level of the bottle.
Upon detecting an underfilled bottle (failure), the system signals the course switch to reject the bottle. The operator’s display shows rejected bottles and statistics for the current process.
In addition, machine vision systems can also measure objects. For example, it is necessary to determine the deviation of the spark plug in the production process. Also, to provide the position information necessary for guiding the robot to prepare the parts. Figure 2 shows how to use a machine vision system to determine the pass / fail of an oil filter (right) and how to measure the tab width in the center of the bracket (left).
Benefits of machine vision
The best way to judge complex and irregular things is to use the human eye. However, when measuring systematic things as numerical values, it claims that machine vision is superior in terms of speed, accuracy, and reproducibility.
For example, on a production line, a single machine vision system can inspect hundreds or thousands of parts per minute. A machine vision system built with a camera and optical system of appropriate resolution can easily inspect subtle features of an object that look too small to judge by the human eye.
Machine vision can perform various inspections without physical contact between the system and the parts to inspection, reducing damage to parts and reducing maintenance time and costs associated with wear and tear of mechanical parts. It is also possible to increase safety by reducing the area of human involvement in the process. It is also useful for preventing contamination of clean rooms.
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