Machine Vision Technology is an important branch of computer science, it integrates optical, mechanical, electronic, computer hardware and software technology, involving computer, image processing, pattern recognition, artificial intelligence, signal processing, optical and electromechanical integration and other fields. Since the beginning of development, has more than 20 years of history, its function and application scope with the development of industrial automation gradually improve and promote, especially the current digital image sensor, CMOS and CCD cameras, DSP, FPGA, arm and other embedded technology, image processing and pattern recognition technology rapid development , and greatly promoted the development of machine vision.
In short, machine vision is the use of machines instead of human eyes to make various measurements and judgments. In the production line, people to do such measurements and judgments due to fatigue, personal differences and other errors and errors, but the machine will be tireless and stable to go on. In general, machine vision systems include lighting systems, lenses, camera systems, and image processing systems. For each application, we need to consider the operating speed of the system and image processing speed, the use of color or black and white cameras, the size of the detection target or the detection of the target is not defective, the field of view needs, the resolution needs to be high, the contrast needs how big. From the functional point of view, the typical machine vision system can be divided into: Image acquisition part, image processing part and motion control part.
The main working process of a complete machine vision system is as follows:
1. The workpiece position detector detects that the object has moved to the visual center of the camera system and sends a trigger pulse to the image acquisition part.
2, the image acquisition part in accordance with the pre-set program and delay, respectively, to the camera and lighting system issued a start pulse.
3. The camera stops the current scan, restarts a new frame scan, or the camera waits before the start pulse arrives, and initiates a frame scan after the start of the pulse.
4, the camera starts a new frame scan before opening the exposure mechanism, exposure time can be set beforehand.
5, another start pulse to turn on the lighting, the time of the light should match the exposure time of the camera.
6, after the camera exposure, formally start a frame image scanning and output.
7, the image acquisition part receives the analog video signal through the A/D to digitize it, or directly receives the camera digitized digital video data.
8, the image acquisition portion of the digital image stored in the processor or computer memory.
9, the processor to the image processing, analysis, recognition, to obtain measurement results or logical control values.
10, the processing results control the movement of the pipeline, positioning, correcting the error of motion.
From the above work flow can be seen, machine vision is a more complex system. Because most of the system monitoring objects are moving objects, the matching and coordination of the system and the moving object is particularly important, so the action time and processing speed of the system are brought to strict requirements. In some applications, such as robots, flight object guidance, etc., there are stringent requirements for weight, volume, and power consumption of the entire system or part of the system.
The advantages of the machine vision system are:
1, non-contact measurement, the observer and the observed will not have any damage, thereby improving the system's reliability.
2, with a wide range of spectral response, such as the use of human invisible infrared measurement, expanding the visual range of the human eye.
3, long-time stable work, it is difficult for humans to observe the same object for a long time, and machine vision can be used for a long time to measure, analyze and identify tasks.
The application field of machine vision system is more and more extensive. In the industry, agriculture, defense, transportation, medical, financial and even sports, entertainment and other industries have been widely used, can be said to have been deep into our lives, production and work in all aspects.
