A Coarse-to-Fine Approach for Layout Analysis of Ancient Manuscripts

Abedelkadir Asi, Rafi Cohen, Klara Kedem, Jihad El-Sana, Itshak Dinstein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Scopus citations

Abstract

Many applications along the manuscript analysis pipeline rely on the accuracy of pre-processing steps. Perfectly detecting the main text area in ancient historical documents is of great importance for these applications. We propose a learning-free approach to detect the main text area in ancient manuscripts. First, we coarsely segment the main text area by using a texture-based filter. Then, we refine the segmentation by formulating the problem as an energy minimization task and achieving the minimum using graph cuts. The energy function is derived from properties of the text components. Spatial coherence of the segmented text regions is explicitly encouraged by the energy function. We evaluate the suggested method on a publicly available dataset of 38 historical document images. Experiments show that the suggested approach outperforms another state-of-the-art page segmentation method in terms of segmentation quality and time performance.

Original languageEnglish
Title of host publicationProceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages140-145
Number of pages6
ISBN (Electronic)9781479943340
DOIs
StatePublished - 9 Dec 2014
Event14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 - Hersonissos, Crete Island, Greece
Duration: 1 Sep 20144 Sep 2014

Publication series

NameProceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Volume2014-December
ISSN (Print)2167-6445
ISSN (Electronic)2167-6453

Conference

Conference14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014
Country/TerritoryGreece
CityHersonissos, Crete Island
Period1/09/144/09/14

Keywords

  • Graph Cuts
  • Historical Documents
  • Layout Analysis
  • Page Segmentation
  • Statistical Inference

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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