EMBEDDED VISION


A compact embedded vision system using Vision Components modules


there isn’t a common MIPI camera control interface for processing units, so processors aren’t easily interchangeable. In this regard, every combination of MIPI camera and processor needs a specific driver. ‘As long as the driver is offered together with the MIPI camera module, then development is quite easy – it’s a standard Linux OS and a Linux driver to access the camera,’ Schmitt said. ‘Where issues can occur is in making sure the driver is available, or having a MIPI camera manufacturer that offers a driver together with the hardware.’ Engineers – at least those outside the


industrial vision space – tend to start by choosing the processor board and then picking the image sensor. Vision Components offers purely MIPI camera modules together with the standard drivers in source code for custom adaptation options, to give the engineer full flexibility of processor choice. Tere are other interfaces that are often


used, such as LVDS, but MIPI is now being included in a lot of newer embedded boards. Meanwhile, on the image sensor side, Sony has developed its SLVS-EC high- speed interface – standing for Scalable Low- Voltage Signalling with Embedded Clock – which has potential for embedded vision system design, although specific drivers are still needed. In the industrial vision world EmVision, a standardisation initiative led by


www.imveurope.com | @imveurope


the European Machine Vision Association, aims to develop a camera API standard for embedded vision systems.


Choosing a platform According to Schmitt, there are four platforms that are getting attention at the moment: Nvidia; Raspberry Pi for rapid prototyping; a growing interest in NXP; and FPGA-based solutions. FPGA is the most complex of these four,


Schmitt said, but there are companies very familiar with FPGA programming, and a MIPI camera module attached to an FPGA can give a product with a long lifespan. Schmitt added that each of the other


three platforms are fairly similar to develop on, as long as the drivers are available. ‘Te Raspberry Pi is still a closed system in some ways, because if you are not using the official Raspberry camera, you have no access to the internal ISP. It’s easy, but it’s limited,’ he said. ‘Nvidia Jetson is a bit more complex, but you have many more options – you have access to the GPU and ISP functions. ‘I wouldn’t say any of the three other


platforms stand out as being easier to use, because for each there are advantages and disadvantages.’ Te German firm Phytec concentrates


on NXP solutions for its embedded vision offerings. It has 26 years experience


‘As long as the driver is offered together with the MIPI camera module, then development is quite easy’


building embedded vision solutions, and, like Vision Components, ensures drivers are provided for cameras in its board support package (BSP). Tis package also has support for various vision middleware, including OpenCV, MVTec’s Halcon library, and Tensorflow Lite. Cameras with MIPI interface are available, and the company now offers the NXP i.MX 8 M Plus processor containing a neural processing unit to accelerate AI applications. Along with design, customisation and


rapid prototyping services, Phytec also supplies development kits to give customers easy access to embedded imaging and to let them start developing immediately. Susan Remmert, responsible for strategic partnerships at Phytec, noted that all components in the kit are industrial-grade, so customers can make a prototype very close to what might be the final product. Various industrial vision suppliers are


now offering embedded vision development kits, including Basler, Te Imaging Source,


g FEBRUARY/MARCH 2021 IMAGING AND MACHINE VISION EUROPE 13


Vision Components


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