• DocumentCode
    2504115
  • Title

    Document Image Retrieval Using Feature Combination in Kernel Space

  • Author

    Hassan, Ehtesham ; Chaudhury, Santanu ; Gopal, M.

  • Author_Institution
    Dept. of Electr. Eng., IIT Delhi, Delhi, India
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    2009
  • Lastpage
    2012
  • Abstract
    The paper presents application of multiple features for word based document image indexing and retrieval. A novel framework to perform Multiple Kernel Learning for indexing using the Kernel based Distance Based Hashing is proposed. The Genetic Algorithm based framework is used for optimization. Two different features representing the structural organization of word shape are defined. The optimal combination of both the features for indexing is learned by performing MKL. The retrieval results for document collection belonging to Devanagari script are presented.
  • Keywords
    document image processing; file organisation; genetic algorithms; image retrieval; indexing; learning (artificial intelligence); Devanagari script; distance based hashing; document image retrieval; feature combination; genetic algorithm; kernel space; multiple kernel learning; word based document image indexing; Equations; Gallium; Histograms; Indexing; Kernel; Optimization; Shape; Document Indexing; Multiple Kernel Learning; Shape Descriptor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.495
  • Filename
    5597259