cuit board traceability,” Vision Systems Design,
April 2014, http://bit.ly/VSD-1404-1).
Some companies have even extended this
graphical flowchart interface concept to allow
developers to access the underlying power of
field programmable gate arrays (FPGAs). VisualApplets from Silicon Software (Mannheim,
Germany; https://silicon.software), for example,
is a software programming environment that
allows developers to perform FPGA programming using data flow models. In the company’s
latest version, functions for segmentation, classification and compression are provided as well
as a Fast Fourier transform (FF T) operator that
allows complex band pass filters to be implemented more efficiently (Figure 2).
Like Silicon Software, NI’s LabVIEW FPGA
Module allows FPGA-efficient algorithms such
as image filtering, Bayer decoding and color
space conversion to be performed without using
low-level languages such as VHDL. By doing
so, many compute-intensive image processing
functions can be off-loaded to the FPGA, thus
speeding machine vision applications.
For those wishing to develop machine vision
systems using a variety of open source and com-
mercially available software, development envi-
ronments are now available that allow image
processing algorithms from a number of dif-
Figure 3: Matrox’s Imaging Library (MIL) can now run under the RTX64 RTOS from IntervalZero,
a fact that has been exploited by Kingstar in the development of PC-based software for industrial
motion control and machine vision applications. Development for RTX64 is performed in C/C++
using Visual Studio and a subset of the Windows API. MIL for RTX64 supports image capture
using GigE Vision and supported Matrox frame grabbers.