Developing embedded systems faster2 September 2019, by Ulrich Pontes

Drone with stereo camera. The small white box holds theembedded system, which evaluates the slightly offsetimages from the two cameras in real time in order todetect obstacles. Credit: Fraunhofer IOSB

Whether for the car or the drone: Developingimage processing software for embedded systemstakes a lot of time and is therefore very expensive.Now the Tulipp platform makes it possible todevelop energy-efficient embedded imageprocessing systems more quickly and lessexpensively, with a drastic reduction in time-to-market. The Fraunhofer Institute for Optronics,System Technologies and Image Exploitation IOSBis a member of the EU consortium which simplifiedthe process.

At first glance drones, driver assistance systemsand mobile medical diagnostic equipment don'tappear to have much in common. But in realitythey do: they all make increasing use of imageprocessing components, for example for detectingobstacles and pedestrians. Image processing canalso be used with mobile X-ray equipment toensure adequate image quality at reducedradiation levels, thus considerably reducingradioactive exposure.

In contrast to a workstation computer, where

dimensions and energy consumption are notparticularly critical factors, applications like theserequire for small, lightweight, energy-efficient imageprocessing components that are nevertheless real-time capable. Hardware platforms based onconventional computer architectures andprocessors can't properly meet these requirements.This is why embedded systems using field-programmable gate arrays (FPGAs) are often used.

Field-programmable gate arrays are logiccomponents whose circuit structure can be freelyconfigured using a special type of programing,usually involving the low-level language VHDL.There's a problem, however: The majority of imageprocessing applications are written in higher-levelprogramming languages such as C/C++, and theirmigration to the embedded systems is highlycomplicated. Not only does VHDL differ greatlyfrom other programming languages, but the codemust also be adapted to the specific hardware. Thismeans even existing VHDL programs can't betransferred to other hardware. Software developershave to start virtually from scratch with every newsystem.

Starter kit for rapidly implementing especiallyenergy-efficient embedded systems

The stereo camera and the embedded system installedon the drone. Credit: Fraunhofer IOSB

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A consortium of eight partners from six countries,including the Fraunhofer Institute for Optronics,System Technologies and Image Exploitation IOSBin Karlsruhe, has now considerably simplified thisprocedure in the Tulipp project. "The result is adevelopment platform consisting of designguidelines, a configurable hardware platform and areal-time-capable operating system that supportsmulticore processors, as well as a programing toolchain," says Dr.-Ing. Igor Tchouchenkov, groupmanager at Fraunhofer IOSB. "A starter kit put onthe market by one of our partners in Tulipp providesadditional support. The starter kit makes developingsuch applications much faster and easier. PortingC++ programs to FPGA, which frequently meansseveral months of work for the developer, can behandled within only a few weeks using the Tulippstarter kit."

This means the developer first has to consider,based on the software programmed in C++, whichcode elements should be distributed to whichhardware components and which program stepscould be optimized or parallelized. The formulateddesign guidelines provide help with this task. Thenthe starter kit comes into play. It contains theconfigurable hardware to which the necessarysensors and output devices can be connected, themultiprocessor-capable real-time operating system,and what is called the STHEM toolchain. Theapplications in the toolchain make it possible tooptimize the C++ program in such a way that it canbe ported to the FPGA as easily and quickly aspossible. "One special focus of the toolchain is onenergy optimization: after all, the aim is to designimage processing systems that can be powered bya small battery whenever possible," saysTchouchenkov. "The toolchain makes it possible toindividually display and optimize energyconsumption for each code function."

A hundred times faster than a high-end PC

Video image from one of the drone’s two cameras.Credit: Fraunhofer IOSB

The consortium worked through three specific usecases in order to develop and test the Tulippplatform: The Fraunhofer IOSB research teamaddressed stereo camera based obstacle detectionfor drones, while other project partners worked onpedestrian detection in the vicinity of a car and onlive quality enhancement of X-ray images taken bymobile C-Arms during surgical operations. In Tulippthey ported the corresponding image processingsoftware from C++ to FPGA.

The results are impressive: The processing, whichoriginally took several seconds to analyze a singleimage on a high-end PC, can now run on the dronein real time, i.e. now approximately 30 images areanalyzed per second. "The speed of pedestriandetection algorithm could be increased by a factorof 100: Now the system can analyze 14 images persecond compared to one image every sevenseconds. Enhancement of X-ray image quality byapplying noise-removing image filters allowedreducing the intensity of radiation during surgicaloperations to one fourth of the previous level. At thesame time energy consumption could besignificantly reduced for all three applications.

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The same image with overlaid depth information from thestereo image analysis, highlighting close obstacles in red.The arrow indicates the resulting recommended evasivepath. Credit: Fraunhofer IOSB

Provided by Fraunhofer-GesellschaftAPA citation: Developing embedded systems faster (2019, September 2) retrieved 5 June 2022 from https://techxplore.com/news/2019-09-embedded-faster.html

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