State Estimation in a Document Image and Its Application in Text Block Identification and Text Line Extraction

  • Hyung Il Koo
  • Nam Ik Cho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6312)


This paper proposes a new approach to the estimation of document states such as interline spacing and text line orientation, which facilitates a number of tasks in document image processing. The proposed method can be applied to spatially varying states as well as invariant ones, so that general cases including images of complex layout, camera-captured images, and handwritten ones can also be handled. Specifically, we find CCs (Connected Components) in a document image and assign a state to each of them. Then the states of CCs are estimated using an energy minimization framework, where the cost function is designed based on frequency domain analysis and minimized via graph-cuts. Using the estimated states, we also develop a new algorithm that performs text block identification and text line extraction. Roughly speaking, we can segment an image into text blocks by cutting the distant connections among the CCs (compared to the estimated interline spacing), and we can group the CCs into text lines using a bottom-up grouping along the estimated text line orientation. Experimental results on a variety of document images show that our method is efficient and provides promising results in several document image processing tasks.


State Estimation Delaunay Triangulation Document Image Text Line Text Region 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hyung Il Koo
    • 1
  • Nam Ik Cho
    • 1
  1. 1.INMC, Dept. of EECSSeoul National University 

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