• DocumentCode
    2463617
  • Title

    Automatic image segmentation of old topographic maps and floor plans

  • Author

    Mello, C.A.B. ; Costa, D.C. ; Santos, T. J dos

  • Author_Institution
    Center of Inf., Fed. Univ. of Pernambuco, Recife, Brazil
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    132
  • Lastpage
    137
  • Abstract
    There are several kinds of information that can be achieved in ancient documents. In general, image processing research on this subject works with images of letters or documents. Topographic maps and floor plans are also an important source of information about history. In this paper, we introduce a new algorithm for image segmentation of ancient maps and floor plans. It aims to remove most part of non textual elements leaving just the text. This allows further automatic identification of the map or plan through automatic character recognition techniques. The proposed method uses a new edge detection algorithm, thresholding and connected component analysis. The results are analyzed both qualitatively and quantitatively by comparison with other technique.
  • Keywords
    character recognition; document image processing; edge detection; history; image segmentation; text detection; ancient documents; automatic character recognition techniques; automatic image segmentation; automatic map identification; connected component analysis; edge detection algorithm; floor plans; history; image processing; image thresholding; nontextual element removal; old topographic maps; text elements; Algorithm design and analysis; Floors; Image color analysis; Image edge detection; Image segmentation; Noise; ancient documents; connected components analysis; edge detection; floor plans; segmentation; topographic maps;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6377689
  • Filename
    6377689