• DocumentCode
    1791720
  • Title

    Scalable solar image Retrieval with Lucene

  • Author

    Banda, Juan M. ; Angryk, Rafal A.

  • Author_Institution
    Montana State Univ., Bozeman, MT, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    11
  • Lastpage
    17
  • Abstract
    In this work we present an alternative approach for large-scale retrieval of solar images using the highly-scalable retrieval engine Lucene. While Lucene is widely popular among text- based search engines, significant adjustments need to be made to take advantage of its fast indexing mechanism and highly-scalable architecture to enable search on image repositories. In this work we describe a novel way of representing image feature vectors in order to enable Lucene to perform search and retrieval of similar images. We compare our proposed method with other popular alternatives and provide commentary of the performance as well as the benefits and caveats of the proposed method.
  • Keywords
    Sun; astronomical image processing; content-based retrieval; image retrieval; search engines; Lucene; content-based image retrieval; image feature vectors; image repositories; search engines; solar image retrieval; Big data; Buildings; Feature extraction; Filtering; Image retrieval; Indexes; Servers; Astroinformatics; Big Data Mining; Content-Based Image Retrieval; Image Processing; Image Retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004399
  • Filename
    7004399