Source: cdxiwang.com
A 2D vision system captures flat images through a camera, and then, through image analysis or comparison, identifies objects, revealing their flat features. It can be used for detecting presence/absence, discrete object analysis, pattern alignment, barcode and optical character recognition, and various 2D geometric analyses based on edge detection.
As 2D vision cannot acquire spatial coordinate information of objects, it does not support shape-related measurements such as flatness, surface angles, volume, or distinguishing features of objects with the same color. It also cannot differentiate the position of contacting side objects. 2D vision relies heavily on changes in light and color/grayscale, making measurement accuracy susceptible to variations in lighting conditions.
3D vision systems, on the other hand, use 3D cameras to capture three-dimensional coordinate information for each point in the field of view. Through algorithms, they reconstruct three-dimensional imaging, unaffected by external environments and complex lighting. Compared to 2D imaging technology, 3D vision is more stable, provides a stronger experience, and offers higher security.
After extensive research and development, 3D vision has found widespread applications in various fields such as biometrics, AIoT, consumer electronics, and industrial sectors. It plays a crucial role in the national economy, empowering industries to achieve digitization and intelligence upgrades.