Implementation and Optimization of Embedded Image Processing System

DOI

10.2991/icecee-15.2015.259How to use a DOI?

Keywords

embedded system; optimization process; image processing and analysis; cloud based system implementation.

Abstract

With the fast development of image science and embedded system technique, the need for the combination is bursting. In this paper, the advantages of scalability of the presented embedded vision system can be seen based on the exemplary application room monitoring. Here it's remarkable that the implementation on the low-end system is up to ten times faster than on the medium-size system. This results from the implementation of the PEG-compression in hardware. Indeed this was a lot of work but significantly reduced the hardware costs. Thus we have shown that a possible product, which is based on our vision system, can be optimized (scaled) according the required performance and unit numbers. To modify our work, selected optimization approaches and mathematical foundations are introduced to improve the performance of the system.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuwen Zheng
PY  - 2015/06
DA  - 2015/06
TI  - Implementation and Optimization of Embedded Image Processing System
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1386
EP  - 1391
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.259
DO  - 10.2991/icecee-15.2015.259
ID  - Zheng2015/06
ER  -