Machine vision system analysis A typical vision system generally includes: light source, optical system, camera, image processing unit (or frame grabber), image analysis and processing software, monitor, communication / input / output unit, etc. â– Image acquisition The acquisition of the image actually converts the visual image and intrinsic features of the measured object into data that can be processed by the computer, which directly affects the stability and reliability of the system. Generally use light source, optical system, camera, image processing unit (or image capture card) to obtain the image of the measured object. â– Light source The light source and the important factors that affect the input of the machine vision system, because it directly affects the quality of the input data and at least 30% of the application effect. Since there is no universal machine vision lighting equipment, for each specific application example, the corresponding lighting device should be selected to achieve the best effect. Many industrial machine vision systems use visible light as the light source, mainly because visible light is easily available, inexpensive, and easy to operate. Several commonly used visible light sources are white flag lamps, fluorescent lamps, mercury lamps and sodium lamps. However, one of the biggest disadvantages of these light sources is that light energy cannot be kept stable. Take the fluorescent lamp as an example, in the first 100 hours of use, the light energy will drop by 15%. As the use time increases, the light energy will continue to decline. Therefore, how to keep the light energy stable to a certain extent is an urgent problem to be solved in the practical process. On the other hand, ambient light will change the total light energy irradiated by these light sources on objects, so that the output image data is noisy. Generally, a method of adding a protective screen is adopted to reduce the impact of ambient light. Due to the above-mentioned problems, in today's industrial applications, for certain demanding detection tasks, invisible light such as X-rays and ultrasonic waves are often used as light sources. The lighting system composed of light sources can be divided into: back lighting, forward lighting, structured light and strobe lighting according to its illumination method. Among them, the back illumination is that the object is placed between the light source and the camera, and its advantage is that it can obtain high-contrast images; the forward illumination is that the light source and the camera are located on the same side of the object, this way is easy to install; structure Light illumination is to project a grating or a linear light source onto the measured object, and demodulate the three-dimensional information of the measured object according to their distortion; stroboscopic illumination is to irradiate high-frequency light pulses on the object, requiring the camera's The scanning speed is synchronized with the strobe speed of the light source. â– Optical system For machine vision systems, the image is the only source of information, and the quality of the image is determined by the appropriate choice of the optical system. Generally, errors caused by poor image quality cannot be corrected with software. Machine vision technology combines optical components and imaging electronics, and uses computer control systems to distinguish, measure, classify, and detect components that are passing through automated processing systems. Machine vision systems can usually detect products processed as fast as 100% without reducing the speed of the production line. Since more and more manufacturers are in need of "6-sigma" (less than three millionths of effective units) results, in order to be more competitive in today's quality-conscious market, this ability is very important . In addition, these systems are ideally suited for satisfactory process control (SPC). The main parameters of the optical system are related to the format of the photosensitive surface of the image sensor, and generally include: aperture, field of view, focal length, F-number, etc. â– Camera The camera is actually a photoelectric conversion device, that is, the optical image received by the image sensor is converted into an electrical signal that can be processed by the computer. The photoelectric conversion device is the core device constituting the camera. At present, typical photoelectric conversion devices are vacuum camera tubes, CCD, CMOS image sensors and so on. The vacuum TV camera tube is composed of a camera target sealed in a glass tube cover and an electron gun. The camera target converts the illuminance distribution of the input optical image into a two-dimensional spatial distribution of the corresponding pixel charges on the target surface, which mainly completes the photoelectric conversion and charge storage tasks; the electron gun completes the image signal scanning and pickup process. TV camera tube imaging system has the characteristics of high definition, high sensitivity, wide spectrum and high frame rate imaging. However, since the TV camera tube is a vacuum tube device, its weight, volume and power consumption are relatively large. CCD is currently the most commonly used image sensor for machine vision. It integrates photoelectric conversion, charge storage, charge transfer, and signal reading, and is a typical solid-state imaging device. The outstanding feature of CCD is that charge is used as a signal, but unlike its device, which uses current or voltage as a signal. This type of imaging device forms a charge packet through photoelectric conversion, and then transfers and amplifies the output image signal under the action of a driving pulse. A typical CCD camera is composed of an optical lens, a timing and synchronization signal generator, a vertical driver, and an analog / digital signal processing circuit. The following figure is the principle block diagram of CCD camera. As a functional device, CCD has the advantages of no burns, no hysteresis, low voltage operation, and low power consumption compared with vacuum tubes. The development of CMOS (Complementary Metal Oxide Semiconductor) image sensors first appeared in the early 1970s. In the early 1990s, with the development of VLSI manufacturing process technology, CMOS image sensors developed rapidly. The CMOS image sensor integrates the photosensitive element array, image signal amplifier, signal reading circuit, analog-to-digital conversion circuit, image signal processor and controller on a chip, and also has the advantages of random access for programming of local pixels. At present, CMOS image sensors are widely used for their good integration, low power consumption, wide dynamic range, and almost no smearing of output images. [next] Image processing and analysis In the machine vision system, the main function of the camera is to convert the light signal received by the photosensitive element into a voltage amplitude signal output. To get the digital signal processed and recognized by the computer, the video information needs to be quantized. The frame grabber is an important tool for quantizing video information. â– Image acquisition / processing card The frame grabber mainly completes the process of digitizing analog video signals. The video signal is first filtered by a low-pass filter and converted into a continuous analog signal in time; in accordance with the image resolution requirements of the application system, the sample / hold circuit must be used to sample the border video signal in time to convert the video The signal is converted into a discrete analog signal; then it is converted into a digital signal output by the A / D converter. While the image acquisition / processing card has analog-to-digital conversion functions, it also has video image analysis and processing functions, and can effectively control the camera at the same time. â– Image processing software In the machine vision system, the processing technology of visual information mainly depends on the image processing method, which includes image enhancement, data encoding and transmission, smoothing, edge sharpening, segmentation, feature extraction, image recognition and understanding. After these processes, the quality of the output image is improved to a considerable extent, which not only improves the visual effect of the image, but also facilitates the analysis, processing and recognition of the image by the computer. Application of machine vision system The machine vision system is an effective way to achieve precise control, intelligence and automation of instruments and equipment. It can be called the "machine eye" of modern industrial production. Its biggest advantages are: (1) Realize non-contact measurement. It will not cause any damage to the observation and the observed person, thereby improving the reliability of the system; (2) It has a wider spectral response range. Machine vision can use special photosensitive elements to observe the world that humans cannot see, thus expanding the human visual range. (3) Work long hours. It is difficult for humans to observe the same object for a long time. The machine vision system can perform observation, analysis and recognition tasks for a long time, and can be applied to harsh working environments.
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