Learning free line detection in manuscripts using distance transform graph

Majeed Kassis, Jihad El-Sana

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

Abstract

We present a fully automated learning free method, for line detection in manuscripts. We begin by separating components that span over multiple lines, then we remove noise, and small connected components such as diacritics. We apply a distance transform on the image to create the image skeleton. The skeleton is pruned, its vertexes and edges are detected, in order to generate the initial document graph. We calculate the vertex v-score using its t-score and l-score quantifying its distance from being an absolute link in a line. In a greedy manner we classify each edge in the graph either a link, a bridge or a conflict edge. We merge every two edges classified as link together, then we merge the conflict edges next. Finally we remove the bridge edges from the graph generating the final form of the graph. Each edge in the graph equals to one extracted line. We applied the method on the DIVA-hisDB dataset on both public and private sections. The public section participated in the recently conducted Layout Analysis for Challenging Medieval Manuscripts Competition, and we have achieved results surpassing the vast majority of these systems.

Original languageEnglish
Title of host publicationProceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019
PublisherIEEE Computer Society
Pages222-227
Number of pages6
ISBN (Electronic)9781728128610
DOIs
StatePublished - 1 Sep 2019
Event15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019 - Sydney, Australia
Duration: 20 Sep 201925 Sep 2019

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)1520-5363

Conference

Conference15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019
Country/TerritoryAustralia
CitySydney
Period20/09/1925/09/19

Keywords

  • Distancetransform
  • Document-graph
  • Learning-free
  • Line-detection

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