• DocumentCode
    248416
  • Title

    A complex network based feature extraction for image retrieval

  • Author

    Jieqi Kang ; Shan Lu ; Weibo Gong ; Kelly, P.A.

  • Author_Institution
    Electr. & Comput. Eng. Dept., Univ. of Massachusetts, Amherst, MA, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    2051
  • Lastpage
    2055
  • Abstract
    In this paper, we propose a complex network based low-level feature for image retrieval systems based on the graph representation of the image and the mathematical theory of diffusion over manifolds. We show that the proposed image feature is invariant to non-structural changes on images and performs well in hand written digits classification task. We also show that performance of image retrieval with existing low-level features could be improved by combining with the proposed feature.
  • Keywords
    complex networks; content-based retrieval; feature extraction; graph theory; handwritten character recognition; image classification; image representation; image retrieval; complex network based feature extraction; graph representation; hand written digit classification task; image retrieval systems; low-level feature system; mathematical diffusion theory; nonstructural changes; Feature extraction; Heating; Histograms; Image edge detection; Image retrieval; Laplace equations; Spectrogram;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025411
  • Filename
    7025411