An article on understanding 3D detection sensors in the field of industrial machine vision
In recent years, machine vision technology has become increasingly complex, and image processing in the industrial field has focused more on 3D sensors. More and more technologies have been improved and put into practical applications, including weld seam detection, as well as sorting or measuring metal plates for unclassified components in the production process. It can be said that machine vision has shifted to 3D.
In the past few years, point cloud evaluation and measurement software has also undergone rapid development: converting from a single image data to point cloud data, measuring, counting, and matching point cloud data. As most players in the image processing industry know, there are several different ways to obtain 3D images.
Spectral confocal measurement
The spectral confocal sensor, due to its detection principle based on white light dispersion, uses a special lens system to extend the focus halo range of different monochromatic lights when white light passes through a small hole. Then, the wavelength of the reflected light on the surface of the measured object is calculated, which can obtain accurate distance data from the measured object to the lens. This means that the measurement process is not affected by the intensity of the reflected light, Almost all objects of any material can achieve high-precision detection.
Spectral confocal method is a new detection technology, which can obtain 3D imaging information of the entire surface/part of the measured object in one scan. It has the characteristics of high detection accuracy, fast speed, and good stability. Spectral confocal sensors are a supplement to or even a substitute for traditional laser detection methods, as they effectively solve the problem of high-precision appearance detection for transparent objects, high reflective mirrors, and strong absorbing materials in the industry. They are very suitable as online detection tools in industries such as 3C electronics, semiconductors, lithium new energy sources, and precision hardware.
Laser triangulation
The traditional laser triangulation method can be used for vertical fields such as wood, rubber, and tires, as well as measurement of automobiles and axles, metal and cast iron industries, or other applications such as road surface measurement.
For laser triangulation, it is necessary to calibrate the camera on a structured light source (such as a laser line projection) to ensure that a high sampling rate above 1 kHz can be obtained even at high ambient temperatures. Usually, the test object moves below the 3D sensor to capture the 3D point cloud. This means that the camera will detect laser lines projected onto the object and calculate height information based on the contour of the laser lines. When moving objects under the camera, multiple configuration files are created to complete the 3D image. A typical setup includes a laser located directly between the test object and the camera, with the camera installed at a 30 ° angle to the laser. But other angle combinations of lasers and cameras are also possible. For example, in order to achieve more accurate height resolution, the angle between the camera and the laser can be widened. But it must be noted that the smaller the angle, the more light enters the camera, and the evaluation results will be more stable. More and more software is available now to process 3D image data. This software can convert captured data into point clouds for direct comparison, making analysis easier.
Stripe projection
In addition to the laser triangulation method, there is also a method called "stripe projection". The basic principle is also triangulation, but testing is beneficial for
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