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Machine vision technology is undergoing a transformation from 2D to 3D, a shift that is not only technologically feasible but also becoming a necessary direction due to the increasing demands of industry applications. 3D vision technology, by endowing intelligent devices with functions similar to the human eye, enables more precise object recognition, detection, and measurement.
In the past, 2D machine vision technology primarily relied on grayscale or color contrast features in images to provide results and has been widely used in automation and quality control processes. However, as requirements for the recognition of complex objects and precision in dimensional measurement have increased, 2D technology has gradually been unable to meet these demands, thus fostering the growth of 3D vision technology.
3D vision technology utilizes near-infrared light to scan the environment and then converts the reflected light into digital signals through CMOS image sensors. Finally, the chip calculates the distance and relative position of objects in three-dimensional space, thereby enabling the development of motion-controlled computer interactions and the detection of objects in the vicinity.
The transition from 2D to 3D requires a leap in the quality and quantity of information obtained. While the 2D vision market has a deep foundation, 3D vision solutions can only fully realize the shift from 2D to 3D once they have reached a certain level of maturity.
The industry consensus is that the transition from 2D to 3D will become the fourth revolution after the transition from black and white to color, from low resolution to high resolution, and from static images to motion pictures.
However, 3D machine vision technology has high technical barriers, involving interdisciplinary design issues such as optics, structure, and thermal management, as well as complex system design composed of chips and algorithms. It requires significant technical strength, substantial investment, and time and talent to develop relevant solutions. High technical barriers, large investments, and few research and development companies are all obstacles on the path to the development of 3D vision.
After the rise of 3D vision, whether to choose 2D or 3D vision has become a controversial issue. Some industry insiders believe that 3D vision will completely replace 2D vision; others argue that 3D vision is expensive and unnecessary in situations where 2D vision can be applied; of course, there is also a third party view that 2D and 3D vision can be integrated and applied.
From a technical perspective, the acquisition of 2D color and 3D geometric data is carried out through two different physical channels.
In terms of implementation, 3D is currently mainly applied in large-scale industrial manufacturing enterprises, logistics, smart city surveillance, and a few consumer application scenarios. From exploration to breakthroughs, it is gradually flourishing on the road to implementation.
There are four mainstream 3D vision technologies in the market currently: binocular vision, TOF, structured light 3D imaging, and laser triangulation.
- Binocular Vision
Binocular technology is a widely used 3D vision system. Its principle is similar to human eyes, using two viewpoints to observe the same object to obtain perceptual images from different perspectives. Then, by calculating the image disparity through the principle of triangulation, the three-dimensional information of the object is obtained.
Due to its simple principle, binocular technology does not require special emitters and receivers; it can obtain three-dimensional information under natural light, so it has the advantages of a simple system structure, flexible implementation, and low cost. It is suitable for online manufacturing, product inspection, and quality control, but its disadvantage is that the algorithm is complex, the computational load is large, and the performance is poor in low light or overexposed conditions.
- 3D Structured Light Technology
Structured light technology projects a structured light, which is not ordinary light but has a certain structure (such as black and white stripes) onto the surface of the object to be measured. Due to the different shapes of objects, these stripes or spots will undergo different deformations. With such deformations, the distance, shape, size, and other information of the object can be calculated to obtain the three-dimensional image of the object through algorithms.
- Laser Triangulation Method
It is based on the optical triangulation principle, which determines the three-dimensional coordinates of spatial objects based on the geometric imaging relationship between the light source, the object, and the detector.
Typically, a laser is used as the light source, and a CCD camera is used as the detector. It has the advantages of structured light 3D vision, such as precision, speed, and low cost.
- TOF (Time Of Flight) Imaging Technology
TOF stands for Time Of Flight. Its principle involves continuously sending light pulses to the target object, then using a sensor to receive the light returned from the object, and by detecting the flight time of the light pulse, the distance to the target object is obtained.
TOF's core components are the light source and the photoreceptive module. Since TOF directly outputs depth information without the need for algorithms used in binocular vision to calculate, it has the advantages of fast response, simple software, and long detection range. Moreover, since it does not require the acquisition and analysis of grayscale images, it is not affected by the properties of external light sources or object surfaces. A typical TOF 3D scanning system can measure the distance of 10,000 to 100,000 points on an object per second. However, the disadvantages of TOF technology are low resolution, inability to produce precise images, and high cost.
Overall, whether it is stereoscopic vision, structured light, laser triangulation, or TOF, no technology is better; only the most suitable one can be chosen.
3D May Become the Mainstream
Robotics, autonomous driving, financial payment have already demonstrated a strong demand for 3D vision, and of course, the metaverse, which blends the virtual and the real, as well as AR, VR, and other XR devices and 3D interaction requirements have already highlighted the market. These demands bring a huge market, but it is also an extremely fragmented market.
GGII data shows that by 2023, China's machine vision market size is expected to reach 20.86 billion yuan, of which the 3D vision market size will reach 3.428 billion yuan, and by 2025, China's 3D vision market size is expected to exceed 10 billion yuan. In this future billion-level market, 3D vision will tend to be intelligent, integrated, real-time, high-performance, and multi-scenario applications.
Although 2D vision is currently the mainstream, with the increasing requirements for measurement precision and the increasingly complex conditions of the objects being measured, the shortcomings of the 2D system are becoming more prominent. As 3D vision technology continues to break through, it is incomparable to 2D in terms of precision, flexibility, and speed. Therefore, 3D machine vision detection has the trend of replacing 2D systems, and it is believed that 3D vision will become the mainstream vision system in the future.
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