The study of 3D stereo vision will have important application value, and it is also one of the important topics in the field of computer vision research. The stereo vision system can automatically identify and locate the target within the field of view, and can realize the system's on-site calibration under complex background environment. By identifying and positioning the feature points on the moving body and analyzing the data, the three-dimensional coordinates of the position of the moving body, the attitude and the relative distance between the feature points are further obtained. With the deepening of various studies, its application will also become more and more extensive, providing strong technical support for the development of the industry.
Currently 3D machine vision is mostly used for rating fruits and vegetables, wood, cosmetics, baked goods, electronic components and pharmaceutical products. It can increase the production capacity of qualified products and discard inferior products early in the production process, thereby reducing waste and saving costs. This feature is ideal for imaging product attributes such as height, shape, quantity, and even color.
Most color cameras consist of a single sensor using a color filter array or mosaic. This mosaic typically consists of red, blue, and green (RGB) optical filters that cover the sensor pixels in a specific pattern. Mosaic then decodes the original sensor data into the RGB values of each pixel for decoding. The advent of higher speed and higher performance microprocessors has spawned various new machine vision applications.
Among them, the three-dimensional camera technology can measure the shape and color of objects during production, which helps improve product quality and reduce production costs. Adding color functions further increases the advantages of quality and cost control. Just like the human eye, the color of the product to be inspected perceived by the machine vision camera is different, which depends on the type of lighting source, image sensor and its lens. Most machine vision systems provide gray-scale product image analysis, but in some cases, color machine vision software needs to detect the shape and contour of the product image.
Machine vision designers are now focusing on developing hardware-independent algorithms for colorimetry, better chroma and luminance decomposition, and color mosaic decoding. At the same time, they found that there are more silicon processing engines to choose from in addition to Advanced Micro Devices and Intel's traditional CPUs. ASICs, DSPs, FPGAs, and graphics processing units (GPUs) provide designers with more software algorithm development tools. The existing 3D CCD color imaging on the market, due to its rugged, dust-proof and washable housing, this IP67-rated industrial camera is mainly used in very demanding working environments.
Compared with human eye stereo vision, 3D stereo vision has irreplaceable advantages, such as high precision, strong expansion ability, long continuous working time, not easy to damage, good confidentiality, no training cost, and easy to save and copy results. The application fields of three-dimensional stereo vision technology have become more and more extensive.