• DocumentCode
    1635069
  • Title

    Logo Matching for Document Image Retrieval

  • Author

    Zhu, Guangyu ; Doermann, David

  • Author_Institution
    Univ. of Maryland, College Park, MD, USA
  • fYear
    2009
  • Firstpage
    606
  • Lastpage
    610
  • Abstract
    Graphics detection and recognition are fundamental research problems in document image analysis and retrieval. As one of the most pervasive graphical elements in business and government documents, logos may enable immediate identification of organizational entities and serve extensively as a declaration of a document´s source and ownership. In this work, we developed an automatic logo-based document image retrieval system that handles: (1) Logo detection and segmentation by boosting a cascade of classifiers across multiple image scales; and (2) Logo matching using translation, scale, and rotation invariant shape descriptors and matching algorithms. Our approach is segmentation free and layout independent and we address logo retrieval in an unconstrained setting of 2D feature point matching. Finally, we quantitatively evaluate the effectiveness of our approach using large collections of real-world complex document images.
  • Keywords
    computer graphics; document image processing; image classification; image matching; image retrieval; image segmentation; document image retrieval; graphics detection; graphics recognition; image classifier; logo matching; logo segmentation; rotation invariant shape descriptor; Government; Graphics; Image analysis; Image databases; Image edge detection; Image recognition; Image retrieval; Image segmentation; Shape; Text analysis; Graphics recognition; document image analysis and retrieval; logo detection; logo matching; shape dissimilarity measures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4244-4500-4
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2009.60
  • Filename
    5277579