Globally Optimal Text Line Extraction Based on K-Shortest Paths Algorithm

Liuan Wang, Seiichi Uchida, Wei Fan, Jun Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The task of text line extraction in images is a crucial prerequisite for content-based image understanding applications. In this paper, we propose a novel text line extraction method based on k-shortest paths global optimization in images. Firstly, the candidate connected components are extracted by reformulating it as Maximal Stable Extremal Region (MSER) results in images. Then, the directed graph is built upon the connected component nodes with edges comprising of unary and pairwise cost function. Finally, the text line extraction problem is solved using the k-shortest paths optimization algorithm by taking advantage of the particular structure of the directed graph. Experimental results on public dataset demonstrate the effectiveness of proposed method in comparison with state-of-the-art methods.

Original languageEnglish
Title of host publicationProceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages335-339
Number of pages5
ISBN (Electronic)9781509017928
DOIs
Publication statusPublished - Jun 10 2016
Event12th IAPR International Workshop on Document Analysis Systems, DAS 2016 - Santorini, Greece
Duration: Apr 11 2016Apr 14 2016

Publication series

NameProceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016

Other

Other12th IAPR International Workshop on Document Analysis Systems, DAS 2016
Country/TerritoryGreece
CitySantorini
Period4/11/164/14/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Library and Information Sciences

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