Find a 3D camera for machine vision








The requirements for a 3D camera are as diverse as the applications. Below you will find the most important selection criteria to help you make the right settings in the product filter and find the right camera more quickly.
The field of view (FoV) determines the area that a 3D camera can capture. A larger field of view allows entire components or larger scenes to be captured in a single step. At the same time, the detail resolution decreases because the same sensor area is distributed over a larger scene. If you want to check the finest details, it is therefore better to choose a smaller FoV, while a larger measurement volume is crucial for large objects or conveyor applications.
The working distance specifies the distance between the camera and the object at which reliable measurements are possible. The size, weight, and protection class of the system must also be taken into account, especially if the camera is mounted in confined spaces or on a robot arm. A robust mechanical design and suitable mounting ensure that measurements remain stable even in the presence of vibrations and temperature fluctuations.
The nature of the surface plays a major role in the measurement results. High-gloss or transparent objects often pose a challenge for laser or structured light-based methods because the light is reflected or refracted. Dark, highly absorbent surfaces, on the other hand, produce weaker signals. In such cases, special measures such as blue lasers, polarization filters, or HDR exposures can help. For outdoor applications or applications with highly variable ambient light, methods such as stereo vision or ToF are usually more robust.
The scan rate indicates how fast a 3D camera captures data. There are two different cases:
A high scan rate is crucial when objects move quickly through the system or a robot has to react in real time. At the same time, higher rates also increase the demands on interfaces and computing power.
In addition to the hardware, it is important to consider how well a camera integrates into existing software environments. Standards such as GigE Vision ensure that devices from different manufacturers can be addressed via the same interface. A stable SDK with sample code and drivers for different operating systems greatly facilitates integration. It is also important that the camera supports common 3D data formats so that point clouds can be further processed without additional effort.