• DocumentCode
    2144756
  • Title

    Layout Analysis for Historical Manuscripts Using Sift Features

  • Author

    Garz, Angelika ; Sablatnig, Robert ; Diem, Markus

  • Author_Institution
    Comput. Vision Lab., Vienna Univ. of Technol., Vienna, Austria
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    508
  • Lastpage
    512
  • Abstract
    We propose a layout analysis method for historical manuscripts that relies on the part-based identification of layout entities. A layout entity -- such as letters of the text, initials or headings -- is composed of a set of characteristic segments or structures, which is dissimilar for distinct classes in the manuscripts under consideration. This fact is exploited in order to segment a manuscript page into homogeneous regions. Historical documents traditionally involve challenges such as uneven writing support and varying shapes of characters, fluctuating text lines, changing scripts and writing styles, and variance in the layout itself. Hence, a part-based detection of layout entities is proposed using a multi-stage algorithm for the localization of the entities, based on interest points. Results show that the proposed method is able to locate initials, headings and text areas in ancient manuscripts containing stains, tears and partially faded-out ink sufficiently well.
  • Keywords
    character recognition; document image processing; text analysis; SIFT features; historical manuscript; layout analysis; layout entity; multistage algorithm; part-based identification; scale invariant feature transform; writing styles; Clustering algorithms; Layout; Noise; Robustness; Shape; Support vector machines; Writing; Sift; document layout; handwritten; historical manuscripts; layout analysis; part-based;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4577-1350-7
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2011.108
  • Filename
    6065363