Abstract—The work describes the evaluation of selected
platforms in computing performance on a defined task. The
work includes a description of the individual platforms and
their hardware equipment. The chosen representatives are from
categories of personal computers, embedded devices and
industrial controller with on board FPGA. The evaluation of
selected platforms is executed by the rising difficulty of given
problem by changing the size of input data. In this case, it is the
resolution of the image used by the Canny edge detecting
algorithm. The result of this work is the relative comparison of
the platforms, even with the increase in the volume of data
processed by the algorithm.
This experiment can be used to simplify architecture and
hardware selection in practical applications due to presented
performance in account of time complexity of given task.
Index Terms—Image processing, LabVIEW, FPGA, cRIO.
Jakub Kolarik, Radek Martinek, Jakub Stefansky, and Petr Bilik are with
the Department of Cybernetics and Biomedical Engineering, Faculty of
Electrical Engineering and Computer Science, VSB–Technical University of
Ostrava, Ostrava, Czech Republic (e-mail: jakub.kolarik@vsb.cz,
{jakub.kolarik, radek.martinek, jakub.stefansky, petr.bilik}@vsb.cz).
Jan Nedoma is with the Department of Telecommunications, Faculty of
Electrical Engineering and Computer Science, VSB - Technical University
of Ostrava, Ostrava, Czech Republic (e-mail: jan.nedoma@vsb.cz).
Cite: Jakub Kolarik, Radek Martinek, Jakub Stefansky, Petr Bilik, and Jan Nedoma, "Comparison of Computing Performance of Image Processing on Different HW Platforms," International Journal of Machine Learning and Computing vol. 10, no. 2, pp. 368-373, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).