Develop High Performance Machine Vision in the Blink of an Eye

The growing capabilities of silicon along with improved algorithms means that machine vision is becoming increasingly important since more and more systems can be built in such areas as manufacturing, intelligent traffic management, bar code scanning, counterfeit detection and even sports simulation. Is that a 3X driver? No, it’s a 3 wood.

The traditional approach would use and FPGA for frame-grabbing and then a PC to do image analysis. The FPGA was fast and flexible and could do some pixel level processing; the PC was easy to program and there were lots of open source algorithms. Now the best of both worlds can be combined in a Xilinx Zync-7000 all-programmable system with the FPGA for speed and real-time response and the processor for the software environment. No PC, no cable bottlenecks, small and power efficient. What’s not to like?

Above is a video to show the difference, made at the SPS/IPC Drives conference held in Nuremburg earlier this year. To compare the old way of doing things to the new, Xilinx built two implementations.

• HALCON machine vision software runs on the Cortex-A9 in the Zync but the FPGA fabric is not used. Result: 16 frame per second (fps) with 50% error rate
• FPGA used for image processing. No errors even when running at 90 fps

So how do you program one of these machine vision systems. The old way would be to learn a hardware description language if you don’t already know one (and if you are a software guy you almost certainly don’t). Or you can use embedded Visual Applets (eVA) from Silicon Software and accelerate your productivity. There are over 200 machine vision operators and they map directly into the FPGA. So even though you are a software guy you can do hardware design!

The design entry is done at a very high level. But the code efficiency is very close to hand-crafted HDL. This produces extremely short design cycles. Like 15 minutes. Obviously great for time-to-market, ease of experimentation and more. It is intended for software engineers, application engineers and machine vision experts. FPGA programming skills are not required. The eVA core is completely inside the glue logic all on the same silicon fabric.

Programming is a four step process:
[LIST=1]