Framos released a new line of embedded vision products
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for building embedded vision devices. Te kit consists of: a Dart Bcon for MIPI camera module with five-megapixel resolution; a developer processing board based on a Qualcomm Snapdragon 820 system-on-chip; a
96boards.org-compatible mezzanine board; and accessories such as lenses and cables. Te explosion in activity around sensor
modules for embedded devices has come about because of the computing power now available on processing boards, such as the Zynq system-on-chip from Xilinx, which includes an Arm Cortex-A9 processor plus FPGA, or Nvidia GPUs, or Qualcomm Snapdragon boards. Speaking during a panel discussion
organised by the VDMA at the trade fair, Dr Klaus-Henning Noffz, CEO of Silicon Soſtware, which makes frame grabbers and FPGA programming soſtware, commented
that some smart sensors can now exceed the capabilities of traditional machine vision systems. ‘Tis is disruptive and will change the game, because it will lower the price of image processing,’ he said. ‘Tis will make our [industrial imaging] technology very common and it will make us [machine vision] a key technology for Industry 4.0.’
Embedded projects In some respects, embedded vision has been around in industrial imaging in one form or another for many years. Twiga, a video hardware designer based in Toulouse, France, has been building embedded devices for custom projects for the past eight years. Te company, which has 14 employees, has made systems for Airbus, for a medical device manufacturer, and for an Austrian binocular OEM. It produces around 25,000 imaging
TULIPP EMBEDDED EU PROJECT DEMOS SYSTEMS
The EU initiative Tulipp, which targets embedded systems for image processing, has delivered its first three use cases covering medical x-ray imaging, automotive driver assistance and UAVs. The systems were demonstrated for the first time at Vision 2018 in Stuttgart, Germany. The Tulipp consortium has
developed an embedded computing reference platform over the course of the project, which ran from 2016 to 2018. Tulipp stands for Towards ubiquitous low-power image processing platforms. The medical x-ray imaging demonstrator combines an embedded computing board
with a medical x-ray imaging sensor. It incorporates image enhancement algorithms for x-ray images running at high frame rates. The focus is on improving the
performance of x-ray imaging Mobile C-arms, which provide an internal view of a patient’s body during an operation to aid surgery. The system using Tulipp’s embedded hardware reference platform can reduce radiation dose by 75 per cent, while maintaining the clarity of images.
The driver assistance system
incorporates pedestrian detection algorithms running in real time on an embedded platform. The ADAS demonstrator achieves
a processing time per frame of 66ms, which means that the algorithm reaches the target of running on every second image for a camera operating at 30Hz. Finally, the project partners
have equipped a UAV with real- time obstacle detection and avoidance capabilities, based on a lightweight and low-cost stereo camera setup. Tulipp will hold a practical
workshop on the project at the HiPeac 2019 conference in Valencia, Spain on 22 January. It will also deliver an in-depth tutorial on 23 January at the show. Participants at the HiPeac workshop and tutorial will receive a free Tulipp development kit.
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