What is machine vision? How machine vision works

Machine vision is a branch of artificial intelligence that is developing rapidly. To put it simply, machine vision is the use of machines instead of human eyes to make measurements and judgments. The machine vision system converts the captured target into an image signal through the machine vision product, transmits it to a special image processing system, obtains the morphological information of the photographed target, and converts it into a digital signal according to the pixel distribution, brightness, color and other information; The image system performs various calculations on these signals to extract the characteristics of the target, and then controls the action of the equipment in the field according to the results of the discrimination.

Machine vision is a comprehensive technology, including image processing, mechanical engineering technology, control, electric light source illumination, optical imaging, sensors, analog and digital ** technology, computer software and hardware technology (image enhancement and analysis algorithms, image cards, IO cards, etc.). A typical machine vision application system includes image capture, light source system, image digitization module, digital image processing module, intelligent judgment and decision-making module and mechanical control execution module.

Machine vision systems are characterized by increasing the degree of flexibility and automation of production. 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 to replace artificial vision; At the same time, in the process of mass industrial production, the use of artificial vision to inspect the quality of products is inefficient and the accuracy is not high, and the use of machine vision detection methods can greatly improve the production efficiency and the degree of automation of production. Moreover, machine vision is easy to realize information integration, which is the basic technology to realize computer integrated manufacturing.

The picture above is a typical application of machine vision.

The use of machine vision equipment is to use the machine instead of the human eye to complete the detection, the specific process is to use the industrial camera to collect the image of the detected device, and this acquisition process can be said to be the most important part of machine vision, because to be collected the characteristics of the device need to be detected all reflected, so how to collect the image needs to constantly adjust the light source and camera parameters according to the characteristics of the device, to ensure that the accurate image can be collected needs to be constantly adjusted.

Of course, this time is analog, and then the professional image processing software is used to convert the analog signal into a digital signal; Then calculate it to extract the characteristics of the target to be detected, such as color, whether there are scratches on the surface of the device, whether the specifications are qualified, whether the surface coating is uniform, etc.; The output result is fed back to the mechanical end for the device to be sorted and inspected, and the unqualified parts are selected.

Generally speaking, the working principle of machine vision equipment is to make the robot vision hardware mainly include two parts: image acquisition and vision processing, and image acquisition is composed of lighting system, vision sensor, analog-to-digital converter and frame memory. Robot vision uses vision sensors to obtain a two-dimensional image of the environment, analyze and interpret it through a vision processor, and then convert it into symbols, allowing the robot to recognize objects and determine their position.

Machine vision inspection system adopts CCD camera to convert the detected target into an image signal, transmits to a dedicated image processing system, according to information such as pixel distribution and brightness, color, converts into a digital signal, and the image processing system performs various operations on these signals to extract the characteristics of the target, such as area, quantity, position, length, and then outputs the result according to the preset allowable degree and other conditions, including size, angle, number, qualified or unqualified, whether there is or not, etc., to realize automatic identification function.

Machine vision is a branch of artificial intelligence that is developing rapidly. To put it simply, machine vision is the use of machines instead of human eyes to make measurements and judgments. The machine vision cracking system converts the ingested target into an image signal through machine vision products (i.e., image acquisition device, divided into CMOS and CCD), transmits it to a dedicated image processing system, obtains the morphological information of the photographed target, and converts it into a digital signal according to the pixel distribution, brightness, color and other information; The image system performs various calculations on these signals to extract the characteristics of the target, and then controls the action of the equipment on the scene according to the results of the discrimination.

Machine vision is a branch of artificial intelligence that is developing rapidly. The concept originated in the field of robotics, where optical devices and non-contact sensors automatically receive and process an image of a real object to obtain the required information or a device to control the robot's movement.

Machine vision is the use of machines instead of human eyes to make measurements and judgments. The machine vision system refers to the machine vision product (i.e., the image acquisition device, divided into CMO and CCD) to convert the acquisition target into a picture carrying crack-image letter stool number, which is transmitted to the image processing system of the special hidden travel, and converted into a digital signal according to the pixel distribution, brightness, color and other information; The image system performs various calculations on these signals to extract the characteristics of the target, and then controls the action of the equipment in the field according to the results of the discrimination.

Machine vision is a branch of artificial intelligence that is developing rapidly. The concept originated in the field of robotics, where an image of a real object is automatically received and processed through optical devices and non-contact sensors to obtain the required information or a device for controlling robot movement.

If the robot needs to interact with the outside world, then the robot must first perceive the surrounding environment. Machine vision is one of the most commonly used methods of perceiving the surrounding environment. Here, we will briefly introduce some basic concepts in the field of machine vision.

Machine vision is a huge field, and here we will only introduce its application in industrial robots. Through the introduction of this article, we will be able to build a simple machine vision system by ourselves, for example, we can determine the position of objects in the room through images, and determine the shape of objects. Further, machine vision can be combined with robot dynamics, so that the robot can be manipulated to complete some specific tasks, such as object handling, grasping, etc.

First, we will discuss the geometry of image formation, which in turn will make it possible to grasp the relationship between actual objects in the real world and their representation in images. Then, we will discuss how to determine some of the key parameters in the above relationship. Then, the above image is segmented to obtain the background description and the object description in the image.

Further, we will discuss the case where there are multiple objects in the image. Finally, we will learn to determine the actual position of an object in the real world using the position of the object's projection in the image.

Machine vision technology is now used in product defect detection, that is, the use of image processing and analysis to detect possible defects in products. When a product is detected for a defect, the image appears to be a difference between the gray value at the defect and the standard image here. Firstly, the features of the defective image are extracted and selected, and then the gray value of the defective image is compared with the gray value of the standard image to determine whether the difference exceeds the preset threshold range, and whether the defect of the product to be detected can be judged by this method.

The machine vision industry will have strong growth for a long time in the future, and the status and role of machine vision will become more and more important as the manufacturing industry upgrades from automation to digitalization and then to intelligence.

As an industrial power, China is expected to release a huge market demand for machine vision systems in the process of industrial upgrading in the future.

For example, in the production process of fabrics, such as cloth quality inspection, such a highly repetitive and intelligent work can only be completed by manual inspection, and a lot of inspection workers can often be seen behind the modern assembly line to perform this process, which increases the huge labor cost and management cost of the enterprise, but still cannot guarantee 100% inspection pass rate (i.e., "zero defect"). Inspecting the quality of cloth is repetitive, error-prone and inefficient.

The assembly line is automatically transformed to make the cloth production line a fast, real-time, accurate and efficient assembly line. On the assembly line, the color and quantity of all fabrics are automatically checked (hereinafter referred to as "cloth inspection"). The automatic recognition technology of machine vision is used to complete the work that was previously done by humans.

In the large-scale cloth inspection, the product quality is inefficient and the accuracy is not high when manually inspected, and the machine vision inspection method can greatly improve the production efficiency and the degree of automation of production.

Why replace artificial vision with machine vision.

There are many reasons for this, but here are a few of the most important ones:

1. From the perspective of production efficiency, because the operator is easy to get tired under long-term work, the quality efficiency of artificial vision is low and the accuracy is not high, while machine vision can greatly improve production efficiency and automation.

2. From the perspective of cost control, training a qualified operator requires enterprise managers to spend a lot of manpower and material resources, but simple training is far from enough, and it takes a lot of time to follow-up to improve the level of operators in practice. Machine vision systems, on the other hand, can be used uninterrupted for a long time without interruption while ensuring production results as long as they are properly designed, commissioned, and operated.

3. In some special industrial environments, artificial vision may pose a threat to the personal safety of operators, and machine vision effectively avoids these risks to some extent.