Machine vision is an interdisciplinary field that encompasses multiple fields, including image processing, computer vision, artificial intelligence, and more. It mainly utilizes image sensors, computers, and other related devices to simulate the functions of the human visual system, and achieves automated detection, recognition, measurement, and control tasks through the collection, processing, and analysis of image or video data.
Machine vision has a wide range of applications, including industrial automation, intelligent transportation, medical diagnosis, safety monitoring, agricultural automation, smart cities, and other fields. In the field of industrial automation, machine vision is mainly used for product quality inspection, production line automation control, logistics sorting, and so on. In the medical field, machine vision can assist doctors in disease diagnosis and treatment, such as using deep learning technology for lesion detection and analysis.
With the continuous development of artificial intelligence technology, the application prospects of machine vision are also becoming increasingly broad. In the future, machine vision technology will be further combined with robot technology, Internet of Things technology, and other technologies to achieve more efficient and intelligent automation applications.
What is the working principle of machine vision equipment?
The working principle of machine vision equipment mainly includes the following steps:
Use a CCD camera to convert the detected target into an image signal and transmit it to a dedicated image processing system.
Transform into digital signals based on pixel distribution, brightness, color, and other information.
The image processing system performs various operations on these signals to extract the features of the target, such as area, quantity, position, and length.
Output results based on preset tolerance and other conditions, including size, angle, number, pass/fail, yes/no, etc., to achieve automatic recognition function.
What are the key technologies of machine vision?
The key technologies of machine vision include:
Lighting source: Lighting directly acts on the original input of the system and has a direct impact on the quality of input data.
Lens: The main function of the lens is to focus the optical image of the target on the photosensitive array of the image sensor (camera).
Image sensor: An image sensor is a device that converts optical images into electrical signals, and its performance directly affects the overall performance of a machine vision system.
Image processing system: Image processing systems can perform various operations on images to extract useful information.
What optical knowledge is applied to machine vision?
Machine vision applies the following optical knowledge:
The propagation law of light. This includes linear propagation of light, reflection of light, refraction of light, interference of light, etc.
Optical imaging. This includes the imaging principles and methods of optical components such as lenses, convex lenses, and reflectors.
Camera structure and lens. This includes the structure and working principle of the camera, as well as different types of lenses (such as fixed focus lenses and zoom lenses).
In addition, machine vision also involves characteristics such as color and intensity of light, as well as related knowledge such as optical measurement and recognition.
What are the classification and characteristics of machine vision light sources?
The classification and characteristics of machine vision light sources are as follows:
Circular light source (vertical illumination type): installed with high brightness LED and high density, providing colors such as infrared, blue, white, red, and green; Not only does it have a large lighting area, but it also has good uniformity of lighting, making it mainly suitable for larger lighting areas.
Circular light source (angle illumination type): installed with ultra-high brightness LED high-density, providing colors such as infrared, red, blue, white, and green; At a certain working distance, the concentrated brightness of the beam is high, the uniformity is good, and the irradiation area is relatively small.
In addition, there are backlights, strip light sources, coaxial light sources, etc.
What are the effects of light sources on machine vision?
The impact of light sources on machine vision includes:
Light source brightness: The brightness of the light source determines the intensity of light that the machine vision system can capture. Higher light source brightness can provide stronger illumination, allowing the system to operate normally in low light environments.
Light source color: The color of the light source is very important for object color recognition and measurement. The color of the light source can be adjusted according to the application requirements, such as using different filters or LED lights.
Light source stability: The stability of the light source determines that the machine vision system can continuously provide stable lighting. A stable light source can ensure the accuracy and consistency of the measurement and analysis results of the system.