Text-Line Extraction as Selection of Paths in the Neighbor Graph

  • Koichi Kise
  • Motoi Iwata
  • Andreas Dengel
  • Keinosuke Matsumoto
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1655)

Abstract

This paper presents a new method of text-line extraction which can be applied to tilted non-rectangular pages. The method is characterized as follows. As the representation of physical structure of a page, we propose the neighbor graph which represents neighbors of connected components. The use of the area Voronoi diagram enables us to extract neighbors without predetermined parameters. Based on the neighbor graph, the task of text-line extraction is considered to be the selection of its paths appropriate as text-lines. We apply simple iterative selection of edges with local examination so as to reduce the computational cost. From experimental results for 50 pages with rectangular and non-rectangular layout, we discuss advantages and limitations of our method.

Keywords

Voronoi Diagram Neighbor Graph Neighbor Relation Voronoi Region Connected Component Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Reference

  1. 1.
    L. A. Fletcher and R. Kasturi, A robust algorithm for text string separation from mixed text/graphics images, IEEE Trans. PAMI, Vol. 10, No. 6, pp.910–918, 1988.Google Scholar
  2. 2.
    L. O’Gorman, The document spectrum for page layout analysis, IEEE Trans. Pattern Anal. & Machine Intell., Vol. 15, No. 11, pp.1162–1173, 1993.CrossRefGoogle Scholar
  3. 3.
    F. Hönes and J. Lichter. Layout extraction of mixed mode documents, Machine Vision and Applications, Vol. 7, pp.237–246, 1994.Google Scholar
  4. 4.
    K. Gyohten, T. Sumiya, N. Babaguchi, K. Kakusho and T. Kitahashi, A multiagent based method for extracting characters and character strings, IEICE Trans.Information & Systems, Japan, Vol. E97-D, No. 5, pp.450–455, 1996.Google Scholar
  5. 5.
    K. Sugihara, Approximation of generalized Voronoi diagrams by ordinary Voronoi Diagrams, CVGIP: Graphical Models and Image Processing, Vol. 55, No. 6, pp.522–531, 1993.CrossRefGoogle Scholar
  6. 6.
    K. Kise, A. Sato and M. Iwata, Segmentation of page images using the area Voronoi diagram, Computer Vision and Image Understanding, Vol. 70, No. 3, pp.370–382, 1998.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Koichi Kise
    • 1
  • Motoi Iwata
    • 1
  • Andreas Dengel
    • 2
  • Keinosuke Matsumoto
    • 1
  1. 1.Department of Computer and Systems Sciences College of EngineeringOsaka Prefecture UniversityGermany
  2. 2.German Research Center for Artificial Intelligence (DFKI, GmbH)KaiserslauternGermany

Personalised recommendations