If large volumes or multiple object views are to be inspected automatically using 3D cameras, such as on continuously running production lines in the automotive industry, high-resolution 3D result data must be generated and processed quickly due to the specified cycle times. Stereo camera systems with large 5 MP sensors and variable baselines provide the ideal output data, but also produce enormous amounts of data. As a result, interfaces and CPU performance can quickly become the limiting bottleneck in such high-performance 3D applications.

The challenge: to reduce data rates and performance requirements for system components without compromising data quality. At the same time, the systems need to be space-saving and efficient. IDS has therefore developed the Ensenso-XR series of embedded 3D cameras with integrated data processing.

In machine vision applications with 3D cameras that work according to the principle of spatial vision (stereo vision), camera images are processed at a high resolution and frame rate in order to make the resulting data available to downstream processes as quickly as possible. The calculation of the three-dimensional data, so-called "point clouds", from the image material of the stereo cameras requires several complex process steps, which were previously performed by powerful industrial PCs (IPCs).

With increasing demands on the quality and speed of this result data, modern 3D stereo cameras, such as the Ensenso X series, use high-resolution 2D cameras with a Gigabit Ethernet interface. However, the transmission of the 2D output data to the processing IPC requires optimal utilization of the network bandwidth in order to avoid time delays or data loss. Apart from this, the processing performance of the IPC hardware must constantly grow in order not to restrict the overall system.

The performance of such 3D camera systems can be further increased by using high-quality components. Thanks to interchangeable 2D cameras, the flexible design of the Ensenso X series is not tied to specific data interfaces and sensor resolutions and can continue to grow in line with the requirements for speed, object sizes and quality. However, high-resolution, fast GigE cameras, specially shielded cables, high-performance network technology and powerful PC hardware are simply too expensive for some applications. Sufficient space must also be available for these peripherals.

Ensenso is taking a different approach with the XR camera series. According to the principle of the Internet of Things (IoT), each individual component in a "distributed system" has a specific task and generates results that are directly reused by other systems. In the case of a 3D camera, these are three-dimensional coordinates of pixels of a real object.

Onboard 3D processing
Thanks to an SoC (System-on-Chip) integrated in the Ensenso XR projector unit, the camera carries out the 3D processes itself, including stereo analysis. After correction of the lens distortion, the 2D output images are converted into an axis-parallel stereo system by a virtual rotation of the cameras (rectification), which greatly facilitates all subsequent analyses. The matching algorithms for still or moving scenes then search the recorded image pairs for corresponding pixels.