Text line extraction based on integrated k-shortest paths optimization

Liuan Wang, Jun Sun, Seiichi Uchida

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

Abstract

Text in images can be utilized in many image understanding applications due to the exact semantic information. In this paper, we propose a novel integrated k-shortest paths optimization based text line extraction method. Firstly, the candidate text components are extracted by the Maximal Stable Extremal Region (MSER) algorithm on gray, red, green and blue channels. Secondly, one integrated directed graph on red, green, and blue channels are constructed upon the candidate text components, which can effectively incorporate different channels into one framework. Then, the integrated directed graph is transformed guided by the extracted text lines in gray channel to reduced the computational complexity. Finally, we use the k-shortest paths optimization algorithm to extract the text lines by taking advantage of the particular structure of the integrated directed graph. Experimental results demonstrate the effectiveness of the proposed method in comparison with state-of-the-art methods.

Original languageEnglish
Title of host publicationProceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages85-90
Number of pages6
ISBN (Electronic)9781538633465
DOIs
Publication statusPublished - Jun 22 2018
Event13th IAPR International Workshop on Document Analysis Systems, DAS 2018 - Vienna, Austria
Duration: Apr 24 2018Apr 27 2018

Publication series

NameProceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018

Other

Other13th IAPR International Workshop on Document Analysis Systems, DAS 2018
CountryAustria
CityVienna
Period4/24/184/27/18

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

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