In today's highly competitive manufacturing industry, manufacturing plants around the world have to increase costs, expand production, and increase competitiveness by improving the automation and stability of manufacturing systems.

Increasing labor costs, increasing product quality requirements, and an ever-increasing number of automated manufacturing systems have created an urgent need for automated monitoring systems in the manufacturing industry. Machine vision imaging systems are a production line that can replace human eyes. High-speed, high-precision inspection equipment is indispensable in today's automated production systems and needs constant improvement and renewal.

Robot vision makes the robot have a visual perception function and is one of the important parts of the robot system. Robot vision can acquire a two-dimensional image of the environment through a vision sensor, which is analyzed and interpreted by a visual processor, and then converted into symbols, allowing the robot to recognize the object and determine its position. Machine vision is a typical interdisciplinary task involving optics, computer vision, pattern recognition, machine learning, artificial intelligence, statistics, cognitive psychology, and more.

Machine vision was first used in industrial manufacturing. Through the automatic recognition function of machine vision, highly reproducible inspection work on many assembly lines can be completed without relying on people, greatly improving detection efficiency and accuracy. The most basic feature of machine vision systems is the increased flexibility and automation of production.

In some dangerous work environments that are not suitable for manual work or where artificial vision is difficult to meet the requirements, machine vision is often used instead of artificial vision. At the same time, in the process of large-scale repetitive industrial production, the machine vision inspection method can greatly improve the efficiency and automation of production.

A typical machine vision system consists of five parts: illumination, lens, camera, frame grabber and vision processor. As acquisition cards can transfer images to memory more quickly, and computer speeds continue to increase, so in today's machine vision systems, the use of vision processors is diminishing.

The image acquisition card plays an important role in the machine vision system. Compared to typical PCI or AGP-compatible capture cards, images can be quickly transferred to computer memory for processing. Some capture cards have built-in multiplexers that can be connected to multiple cameras and can control the capture card to capture information from any camera.

Along with the vigorous development of China's manufacturing industry, the machine vision industry has also experienced the initial period of development in the Chinese market. Internationally renowned machine vision manufacturers have started their business in China, which has driven the rise of this industry in China. After a certain period of popularization, machine vision has gradually become familiar to customers, and the scope of application has gradually expanded. The large-scale application field has gradually expanded from the initial electronics and pharmaceutical industries to packaging, injection molding, automotive and other fields. There are also a large number of applications in the transportation, printing and other industries.

Its application is more to improve production efficiency and reduce labor costs. Therefore, some artificial links in industrial production and management are gradually being replaced by robots.

Machine vision systems are characterized by increased flexibility and automation. In some dangerous working environments that are not suitable for manual work or where artificial vision is difficult to meet the requirements, machine vision is often used instead of artificial vision; for example, in the process of mass production of plastic products in the injection molding industry, as the first brand of domestic manufacturing automation As an example of the industrial robotic system integrator's Guangdong Tuostar, the machine vision system of robots and industrial robots is widely used in the injection molding industry. Tusta's robots and industrial robots convert the ingested targets into machine vision devices. The image signal is transmitted to a dedicated image processing system and converted into a digitized signal based on pixel distribution and brightness, color, and the like.

The image system performs various operations on these signals to extract the characteristics of the target, thereby realizing rapid drop in the injection molding machine mold, and slowly lowering the outside of the mold, and having the function of “quick and quick release”. The use of artificial visual ingestion to check product quality is inefficient and inaccurate, and machine vision detection methods can greatly improve production efficiency and automation of production. Moreover, machine vision is easy to implement information integration, and is the basic technology to realize computer integrated manufacturing.

China is a typical labor-intensive country, and most industries rely on a large surplus of labor. At the time of the transformation of China's manufacturing industry to automation, machine vision and automation are closely related. On the one hand, it effectively solves the employment problem, on the other hand, it promotes the promotion and use of machine vision-related automation products.

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