A Block Size Optimization Algorithm for Parallel Image Processing

J. Alvaro Fernandez, M. Dolores Moreno

Abstract

The aim of this work is to define a strategy for rectangular block partitioning that can be adapted to the number of available processing units in a parallel processing machine, regardless of the input data size. With this motivation, an algorithm for optimal vector block partitioning is introduced and tested in a typical parallel image application. The proposed algorithm provides a novel partition method that reduces data sharing between blocks and maintains block sizes as equal as possible for any input size.

References

  1. Bailey, D. G., 2011. Design for Embedded Image Processing on FPGAs. Wiley. Singapore, Singapore.
  2. Bovik, A. (ed), 2005. Handbook of Image and Video Processing, 2nd ed. Academic Press, London, UK.
  3. Davies, E. R., 2012. Computer and Machine Vision: Theory, Algorithms, Practicalities, 4th ed. Academic Press, Oxford, UK.
  4. de Smith, M. J., Goodchild, M. F., Longley, P. A., 2013. Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools, 4th ed, The Winchelsea Press. Winchelsea, UK, www: http://www.spatialanalysisonline.com.
  5. Downton, A., Crookes, D., 1998. Parallel Architectures for Image Processing, Electronics and Comm Eng J, 10(3), pp. 139-151, doi: 10.1049/ecej:199803072010.
  6. Fleury, M., Downton, A., 2001. Parallel Processing Farms: Structured Design for Embedded Parallel Systems. Wiley. Singapore, Singapore.
  7. Huang, T. S., Yang, G. J., Tang, G. Y, 1979. A Fast TwoDimensional Median Filtering Algorithm. IEEE Trans Acoustics Speech Signal Proc, 27(1), pp. 13-18, doi: 10.1109/TASSP.1979.1163188.
  8. Kuwahara, M., Hachimura, K., Ehiu, S., Kinoshita, M., 1976. Processing of Ri-Angiocardiographic Images, in Preston, K., Onoe, M. (eds). Digital Processing of Biomedical Images, Plenum Press, pp. 187-202, New York, USA, doi: 10.1007/978-1-4684-0769-3_13.
  9. Mangano, S., 2010. Mathematica Cookbook. O'Reilly. Sebastopol, USA.
  10. Moler, C., 2007. Parallel MATLAB: Multiple Processors and Multiple Cores, The Mathworks News & Notes, www: http://www.mathworks.com/tagteam/42682_ 91467v00_NNR_Cleve_US.pdf.
  11. Ratha, N., Karu, K., Chen, S., Jain, A., 1996. A Real-Time Matching System for Large Fingerprint Database, IEEE Trans Pattern Anal Machine Intell (PAMI), 18(8), pp. 799-813, doi: 10.1109/34.531800.
Download


Paper Citation


in Harvard Style

Alvaro Fernandez J. and Dolores Moreno M. (2014). A Block Size Optimization Algorithm for Parallel Image Processing . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 138-144. DOI: 10.5220/0004695001380144


in Bibtex Style

@conference{visapp14,
author={J. Alvaro Fernandez and M. Dolores Moreno},
title={A Block Size Optimization Algorithm for Parallel Image Processing},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={138-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004695001380144},
isbn={978-989-758-003-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - A Block Size Optimization Algorithm for Parallel Image Processing
SN - 978-989-758-003-1
AU - Alvaro Fernandez J.
AU - Dolores Moreno M.
PY - 2014
SP - 138
EP - 144
DO - 10.5220/0004695001380144