| Peer-Reviewed

Parallel Image Processing Using Algorithmic Skeletons

Received: 30 September 2014     Accepted: 5 October 2014     Published: 17 October 2014
Views:       Downloads:
Abstract

In the last few decades, image processing has achieved significant theoretical and practical progress. It has been so fast that image processing can be easily traced in several disciplines and industries. At present, various methods have been proposed to implement image processing. The present paper aims to present a technique for image processing which utilizes design and analysis of parallel algorithms. It employs a new approach called “algorithmic skeletons” which is composed of a set of programming templates; hence facilitating the programmers’ work.

Published in International Journal of Intelligent Information Systems (Volume 3, Issue 6-1)

This article belongs to the Special Issue Research and Practices in Information Systems and Technologies in Developing Countries

DOI 10.11648/j.ijiis.s.2014030601.12
Page(s) 10-14
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Image Processing, Algorithmic Skeletons, Face Detection and Recognition

References
[1] H. Gonz´alez-V´elez, M. Leyton, “A Survey of Algorithmic Skeleton Frameworks: High-Level Structured Parallel Programming Enablers,” in Research Monographs in Parallel and Distributed Computing. MIT Press, 2008.
[2] Aldinucci, M.; Danelutto, M.; Antoniu, G.; Jan, M. "Fault-Tolerant Data Sharing for High-level Grid: A Hierarchical Storage Architecture". Achievements in European Research on Grid Systems, 2008.
[3] Wang, Q., Wu, J. Long, C. Li, B, “P-FAD: Real-time face detection scheme on embedded smart cameras ,” in Distributed Smart Cameras (ICDSC), 2012 Sixth International Conference,2012.
[4] Y. Hu and J. Hwang, Handbook of neural network signal processing. CRC Press, 2002.
[5] C. H. Chu, E. J.Delp, L.H. Jamieson,H. J. Siegel, F. J.Weil, and A. B. Whinston, “A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture,” Journal of Parallel and Distributed Computing, vol. 6, pp. 598–662, June 1998.
[6] J. Haddadnia, K. Faez, and P. Moallem,“Human face recognition with moment invariants based on shape information,” in Proceedings of the International Conference on Information Systems, Analysis and Syn-thesis, vol. 20, (Orlando, Florida USA), International Institute of Informatics and Systemics(ISAS), 2001.
[7] Mario Leyton, Jose M. Piquer. "Skandium: Multi-core Programming with algorithmic skeletons", IEEE Euro-micro PDP 2010.
[8] G. Yaikhom, M. Cole, S. Gilmore, and J. Hillston. "A structural approach for modelling performance of systems using skeletons." Electronic Notes in Theoretical Computer Science, 190(3):167–183,2007.
[9] N. Zhang, Y. Chen, W. Jian-Li,” Image parallel processing based on GPU ,“ Advanced Computer Control (ICACC), 2010 2nd International Conference, March 2010.
[10] S. Eghtesadi, M. Sandler, “Implementation of the Hough transform for intermediate-level vision on a transputer network”, Journal of Parallel and Distributed Computing, Volume 13, Issue 3, Pages 212–218, April 1989.
[11] R. Boynton, “Measuring weight and all three axes of the center of gravity of a rocket motor without having to re-position the motor”, presentation at the 61st Annual Conference of the Society of Allied Weight Engineers Virginia Beach, Virginia May 20-22, 2002.
[12] Z. Fang , X. Li , “A parallel processing approach to image object labeling problems”, CSC '87 Proceedings of the 15th annual conference on Computer Science, Page 423, New York, 1987.
[13] C.Papamanthou, F. Preparata, R.Tamassia, “Algorithms for Location Estimation Based on RSSI Sampling”, Springer-Verlag Berlin Heidelberg, 2008.
[14] S. Bohlhalter, C.Fretz, B. Weder, “Hierarchical versus parallel processing in tactile object recognition: a behavioural-neuroanatomical study of aperceptive tactile agnosia”, Brain ,2002.
[15] P. Jonker and W. Caarls, “Application driven design of embedded real-time image processing,” in Proceedings of ACIVS 2003 (Advanced Concepts for Intelligent Vision Systems), (Gent, Belgium), 2003.
[16] J. darlingtons, Y. Guo, H.W. To, J. Yang, “Functional Skeletons for Parallel coordination”, proceeding of 1st EuroPar Conference, Stokholm, Sweden, pp. 55-66, Agust 1995.
[17] R. Jones, “Machine vision applications”, science direct, Volume 1, Issue 4, 1991, Pages 439–446.
Cite This Article
  • APA Style

    Sare Eslami Khorami. (2014). Parallel Image Processing Using Algorithmic Skeletons. International Journal of Intelligent Information Systems, 3(6-1), 10-14. https://doi.org/10.11648/j.ijiis.s.2014030601.12

    Copy | Download

    ACS Style

    Sare Eslami Khorami. Parallel Image Processing Using Algorithmic Skeletons. Int. J. Intell. Inf. Syst. 2014, 3(6-1), 10-14. doi: 10.11648/j.ijiis.s.2014030601.12

    Copy | Download

    AMA Style

    Sare Eslami Khorami. Parallel Image Processing Using Algorithmic Skeletons. Int J Intell Inf Syst. 2014;3(6-1):10-14. doi: 10.11648/j.ijiis.s.2014030601.12

    Copy | Download

  • @article{10.11648/j.ijiis.s.2014030601.12,
      author = {Sare Eslami Khorami},
      title = {Parallel Image Processing Using Algorithmic Skeletons},
      journal = {International Journal of Intelligent Information Systems},
      volume = {3},
      number = {6-1},
      pages = {10-14},
      doi = {10.11648/j.ijiis.s.2014030601.12},
      url = {https://doi.org/10.11648/j.ijiis.s.2014030601.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.s.2014030601.12},
      abstract = {In the last few decades, image processing has achieved significant theoretical and practical progress. It has been so fast that image processing can be easily traced in several disciplines and industries. At present, various methods have been proposed to implement image processing. The present paper aims to present a technique for image processing which utilizes design and analysis of parallel algorithms. It employs a new approach called “algorithmic skeletons” which is composed of a set of programming templates; hence facilitating the programmers’ work.},
     year = {2014}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Parallel Image Processing Using Algorithmic Skeletons
    AU  - Sare Eslami Khorami
    Y1  - 2014/10/17
    PY  - 2014
    N1  - https://doi.org/10.11648/j.ijiis.s.2014030601.12
    DO  - 10.11648/j.ijiis.s.2014030601.12
    T2  - International Journal of Intelligent Information Systems
    JF  - International Journal of Intelligent Information Systems
    JO  - International Journal of Intelligent Information Systems
    SP  - 10
    EP  - 14
    PB  - Science Publishing Group
    SN  - 2328-7683
    UR  - https://doi.org/10.11648/j.ijiis.s.2014030601.12
    AB  - In the last few decades, image processing has achieved significant theoretical and practical progress. It has been so fast that image processing can be easily traced in several disciplines and industries. At present, various methods have been proposed to implement image processing. The present paper aims to present a technique for image processing which utilizes design and analysis of parallel algorithms. It employs a new approach called “algorithmic skeletons” which is composed of a set of programming templates; hence facilitating the programmers’ work.
    VL  - 3
    IS  - 6-1
    ER  - 

    Copy | Download

Author Information
  • Islamic Azad University South Tehran Branch, Tehran, Iran

  • Sections