Introduction to the development of machine vision:

In the 1960s, machine vision technology took its first steps in research overseas. With the rapid advancement of large-scale integrated circuits, vision systems gradually moved from the laboratory to practical applications. The rapid rise of microcomputers in the 1980s injected new vitality into machine vision systems, allowing them to penetrate diverse fields such as industry, medicine, agriculture, and transportation, with their application areas continuously refined and deepened. This article will systematically explain the components and operating principles of machine vision systems, providing readers with a clear technical introduction.

Machine vision system components:

Literally, a machine vision system can be divided into three core components: the "machine" responsible for the movement and control of the actuator; the "vision" that captures images using hardware such as lighting, industrial lenses, industrial cameras, and frame grabbers; and the "system" primarily referring to the vision processing software, which can also be understood as the integrated machine vision equipment. Below, we will focus on the five key modules in the system.

Machine vision light source (lighting system)

The lighting source is the starting point of the vision system, and its performance directly determines the quality of image data and the accuracy of subsequent processing. Due to the diversity and complexity of actual application scenarios, there is no "universal lighting solution." Therefore, it is necessary to select an appropriate light source based on the specific object and environment to enhance target features and suppress interfering reflections. Common light source types include: LED ring light sources, low-angle light sources, backlight sources, strip light sources, coaxial light sources, cold light sources, point light sources, linear light sources, and parallel light sources. They are suitable for different applications such as surface defect detection, contour recognition, and character recognition.

Industrial lenses

Industrial lenses, as core optical components, undertake the critical tasks of beam modulation and image signal transmission. Depending on the application requirements, standard lenses, telecentric lenses, wide-angle lenses, close-up lenses, and telephoto lenses can be selected. When selecting a lens, consider the camera interface type, working distance, field of view, sensor size, distortion control, magnification, focal length, and aperture parameters to ensure clear and accurate images.

Industrial cameras

Industrial cameras serve as "visual sensors" within the system, their essential function being to convert optical signals into electrical ones. Compared to conventional cameras, industrial cameras offer greater image stability, stronger interference immunity, and superior data transmission performance. Based on their output method, they can be categorized as analog or digital. Based on their imaging chip type, CCD and CMOS are the two primary types, with the latter gaining widespread adoption in recent years due to its cost and integration advantages.

Frame grabber

The frame grabber is a crucial link between the camera and the processing unit, determining the camera types and image formats supported by the system, such as black-and-white/color, and analog/digital. Common frame grabbers include PCI, 1394, VGA, and GigE. Some high-end cards feature multi-channel input, enabling simultaneous connection to multiple cameras to meet the efficient capture and processing requirements of complex visual tasks.

Machine Vision Software

Vision software is the "brain" of the entire system, enabling image processing, analysis, and decision-making. Secondary development based on algorithm packages can automate a range of tasks, including image acquisition, display, storage, and recognition and judgment. When selecting vision software, it's important to consider its development environment, operating system compatibility, supported programming languages, and ongoing maintenance and expansion capabilities to ensure stable system operation and good scalability.

Principles of Machine Vision Systems: The fundamental goal of a machine vision system is to convert captured targets into digital image signals through image acquisition equipment (including light sources, lenses, cameras, and acquisition cards), transmitting them to specialized image processing software to replace the human eye in performing tasks such as identification, measurement, detection, and judgment. Its core principle is to use computers and related equipment to simulate human visual mechanisms, extracting and processing visual information. With the continuous integration of microelectronics, network communications, and big data, machine vision systems are developing towards greater intelligence, integration, and flexibility. In the future, they will replace human labor in more complex, high-precision, or high-risk scenarios, becoming a key pillar of intelligent manufacturing and artificial intelligence.