Embedded PCs differ from classic IPC systems in that the functionality of the image capture cards is permanently integrated in the embedded PC. © Stemmer

Embedded and freely programmable
Embedded PCs differ from classic IPC systems in that the functionality of the image capture cards is already integrated into the embedded PC. Like classic industrial PCs, they also enable the connection of external standard cameras with all image sensors available on the market. Based on Windows Embedded operating systems, Embedded PCs are also freely programmable and allow flexible adaptation of the systems to the respective requirements via special libraries for industrial image processing. The connection to the machine is established via proprietary bus adapters or special Industrial Ethernet cards. According to Keppler, the Windows environments used have all the known advantages and disadvantages for the user. He cites the CVS Image Station Compact from Stemmer, the IPD GV family from Teledyne Dalsa and the Matrix series from Adlink as examples of embedded PC systems.

Easy to operate and intelligent
Smart cameras and vision sensors go one step further: in these systems, the camera sensor and image capture, the processor for image evaluation and the I/O interfaces, as well as lighting and optics in some cases, are usually combined in a very compact, robust housing. Vision sensors usually have a graphical "point and click" parameterization. These systems often also work with integrated lighting and optics, which simplifies the application but also reduces flexibility, Keppler points out: "Such systems are usually optimized for specific applications and do not allow a switch to a completely different application, for example from pure presence monitoring to measuring or reading tasks. Another limitation is the limited range of image sensors that can be used in such products."

There is no precise definition between smart cameras and vision sensors. Typical representatives of this class are the compact stand-alone products of the Insight family from Cognex and the Boa series from Teledyne Dalsa.

Specialized in one task
For fully integrated image processing systems that can also work without an operating system, Keppler suggests the term deep embedded vision system, which is not yet established on the market. "Such systems are specially developed for a specific task and are not freely programmable. The communication options of such systems are already firmly defined at the design stage and can only be changed at a later date with relatively high effort." The system design of such deep-embedded vision systems incurs high initial costs, which can only be amortized through large quantities. As a rule, such products are characterized by very low power consumption, which enables long operating times even when operated by battery.

A current example of such deep-embedded vision systems is the Realsense technology from Intel. These camera systems are based on the Realsense vision processor D4 with the most advanced algorithms to process the raw image streams from the integrated image sensors and calculate precise 3D depth information with high resolution at an impressive frame rate and output these 3D images as a result for further processing.

Deep embedded vision systems are specially developed for a specific task and are not freely programmable. © Stemmer

Another example of such deep-embedded vision systems comes from the field of text recognition: compact modules with an integrated camera, OCR software and wireless connection are mounted directly on mechanical counters and enable cost-effective automatic recording without replacing the existing counters with electronic versions: They transmit the meter readings directly to the master computer at set intervals. This eliminates the need for manual readings. Due to the extremely low power consumption and the short switch-on phases, these modules have a maintenance-free service life of around ten years.

Extreme flexibility
According to Keppler, System On Chip (Soc) is a young, recently emerging embedded computer technology with extreme flexibility. "Socs allow customized systems and easy adaptation of a wide variety of image sensors via standard cameras and numerous standard interfaces such as GigE Vision, USB3 Vision or MIPI. By integrating powerful hardware such as FPGAs, GPUs or DSPs, they provide local pre-processing and data reduction if required. Standard-compliant image distribution for further processing and standard-compliant machine communication via OPC UA are also possible." According to Keppler, further advantages of such ARM-based systems under Linux when using the right software environment include source code compatibility with PC systems, free programmability via C/C++ and access to image processing libraries with optimized algorithms. Compact designs, simple integration and low power consumption also characterize these systems.

"As Socs only require low initial investment and system costs and can also be easily duplicated, I believe this technology has the potential to revolutionize image processing," says Keppler.

Selecting the optimum system
The world of automation is becoming increasingly complex. Buzzwords such as Industry 4.0, Internet of Things (IoT) and the Industrial Internet of Things (IIoT) extension, cloud computing, distributed computing, artificial intelligence, machine learning and many other technologies are an expression of the many innovative developments that present users and developers of machine vision systems with major challenges when selecting the optimum system for their particular application.

"Against this backdrop, it is becoming increasingly important that users can rely on advice from competent partners for this key technology," Keppler is convinced. "Stemmer has been focusing on industrial image processing for 30 years, has played a decisive role in shaping the development of the industry and covers all the technologies described with its portfolio."

Keppler describes software as the key to the optimal image processing system for the respective application: "It should be independent of the hardware platform and operating system and also be compatible with common source codes and standards in order to offer the necessary flexibility." Here too, Keppler believes that his company is ideally positioned to provide users with the best possible support on the path to successful application development thanks to its in-house software development, the Common Vision Blox software platform that has been established for years and professional support.

Keppler does not believe that classic image processing could soon become obsolete due to the rapid developments in the field of embedded vision: "Embedded vision systems have experienced an enormous upswing in recent years, both in terms of their performance and their versatility, and offer their users flexible options. Nevertheless, there will still be numerous applications in which classic PC-based image processing systems are the optimal solution." Peter Stiefenhöfer/as