• DocumentCode
    3443112
  • Title

    A swarm intelligence based approach for image feature extraction

  • Author

    Lakehal, E.

  • Author_Institution
    Comput. Sci. Dept., Batna Univ., Batna, Algeria
  • fYear
    2009
  • fDate
    2-4 April 2009
  • Firstpage
    31
  • Lastpage
    35
  • Abstract
    This paper presents a new approach to detect points of interest in an image. It uses swarm intelligence to detect centers of objects which are considered as points of high interest because many of psychological works state that the symmetry attracts the attention of human visual system. This fact led to the choice of symmetric objects´ centers as points having a high visual interest and then used as points of interest in object classification and recognition. Earlier works search for points of interest in high signal variations. Unfortunately, with images presenting very limited signal variations, existing approaches seem to be useless. In contrast, the use of approaches dealing with visual interpretability like centers of symmetric objects is suggested to be an interesting research axis. The originality of this work is the use of ant colonies for recognition purpose whereas the major use of ant colonies is to do optimization and classification.
  • Keywords
    feature extraction; image classification; object recognition; optimisation; human visual system; image feature extraction; object classification; object recognition; optimization; point-of-interest; psychological work; swarm intelligence-based approach; Application software; Artificial intelligence; Content based retrieval; Feature extraction; Image retrieval; Lakes; Object detection; Object recognition; Particle swarm optimization; Robustness; Ant colonies; Feature extraction; Points of interest; Swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on
  • Conference_Location
    Ouarzazate
  • Print_ISBN
    978-1-4244-3756-6
  • Electronic_ISBN
    978-1-4244-3757-3
  • Type

    conf

  • DOI
    10.1109/MMCS.2009.5256735
  • Filename
    5256735