Machine vision technology is an interdisciplinary field involving artificial intelligence, neurobiology, psychophysics, computer science, image processing, pattern recognition, and many other areas. Machine vision primarily uses computers to simulate human visual functions, extracting information from images of objective objects, processing and understanding it, and ultimately using it for practical detection, measurement, and control.
What is an industrial camera?
Industrial cameras are a key component of machine vision systems. Their essential function is to convert light signals into ordered electrical signals, essentially acting as the "eyes" of the machine vision system. Compared to traditional consumer cameras (camcorders), industrial cameras (camcorders) offer advantages such as high image stability, high transmission capacity, and high anti-interference capabilities. Most industrial cameras on the market are based on CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) chips.
CCD, or Charge Coupled Device, is an image sensor made of a highly sensitive semiconductor material. It converts light into electrical charges, which are then converted into digital signals by an analog-to-digital converter chip. These digital signals are compressed and stored in the camera's internal flash memory or built-in hard drive, allowing data to be easily transferred to a computer. With the help of computer processing, the image can be modified according to needs and imagination.
CMOS stands for Complementary Metal-Oxide Semiconductor. Like CCD, it is a semiconductor used in digital cameras to record changes in light. The manufacturing technology of CMOS is similar to that of general computer chips. It primarily utilizes semiconductors made of silicon and germanium, allowing N-type (negative) and P-type (positive) semiconductors to coexist on the CMOS. The current generated by the complementary effect of these two semiconductors can be recorded and interpreted by the processing chip as an image.
The role of industrial cameras
Industrial cameras are typically installed on machine production lines to replace human eyes for measurement and judgment. They capture targets through digital imaging, convert them into image signals, and transmit them to a dedicated image processing system. The image system performs various calculations on these signals to extract the target's features, and then controls the on-site equipment based on the judgment results.
With the rapid development of the domestic machine vision industry, industrial cameras, a crucial component of machine vision systems, have also experienced tremendous growth. Digital industrial cameras have no limitations on the size of the object being photographed; depending on the lens, they can photograph general materials as well as be used for microscopic photography. Currently, the main applications of industrial cameras include the following:
(1) In product development and product verification, such as when developing metal and resin materials, it can be used to observe the direction and state of internal cracks when the material is impacted, analyze the structure of the material when it is damaged, and conduct industrial online testing of electronic products.
(2) In the printing process of the packaging and labeling industry, it is possible to detect minute defects in high-speed printing in real time so that measures can be taken to reduce losses. Common defects such as scratches, dust, missing prints, ink marks, and wrinkles can all be detected, improving return on investment, reducing waste expenditures, and increasing customer satisfaction and trust.
(3) Other fields: such as machine vision, scientific research, military science, aerospace and many other fields, especially in the intelligent transportation industry: speeding capture, red light violation electronic police, highway intersections, card toll collection and other transportation industries have also been well used.
Classification of industrial cameras
Before actually purchasing and using industrial cameras, the first thing companies need to determine is the type of camera. Below is a classification of industrial cameras according to different industry standards.
(1) Chip type
Divided into CCD cameras and CMOS cameras;
(2) Structural characteristics of the sensor
Cameras are divided into line scan cameras and area scan cameras;
(3) According to the scanning method
Divided into interlaced scanning cameras and progressive scanning cameras;
(4) Resolution size
Cameras are divided into standard resolution cameras and high resolution cameras;
(5) Output signal mode
Cameras are divided into analog cameras and digital cameras;
(6) Output color
Cameras are divided into monochrome (black and white) cameras and color cameras;
(7) Output signal speed
Divided into ordinary speed cameras and high-speed cameras;
(8) Response frequency range
Cameras are categorized into visible light (ordinary) cameras, infrared cameras, and ultraviolet cameras.
Why do industrial cameras drop frames?
Choosing the right camera is a crucial step in machine vision system design. The camera selection directly determines the resolution and quality of the acquired images, and also relates to the overall system operation. Poorly designed drivers or industrial camera hardware can cause frame drops due to data channel congestion and inability to process data in a timely manner. Therefore, when a new image arrives, the previous image may be forced to be discarded, or a new image may be forced to be discarded. Solving this problem requires designers to meticulously design every aspect of data transmission between the driver and the industrial camera hardware.
Smart cameras and industrial cameras
A smart camera is not simply a camera, but a highly integrated, miniature machine vision system. It integrates image acquisition, processing, and communication functions into a single camera, providing a multifunctional, modular, highly reliable, and easy-to-implement machine vision solution. Furthermore, thanks to the application of the latest DSP, FPGA, and high-capacity storage technologies, its intelligence level is continuously improving, meeting the diverse application needs of machine vision.
Industrial cameras and smart cameras have similar applications, but their usage differs greatly. Industrial cameras require an external controller and specialized software engineers for programming, and can handle various complex testing requirements. Smart cameras, on the other hand, have built-in simple and practical debugging tools, can work independently without an external controller, and are easy to operate and learn.
