Videos with superimposed external subtitles constitute the major part of modern video content. However, there are quite a lot of diverse videos with embedded subtitles as well. In this regard, the problem arises of extracting and converting embedded subtitles into modern formats of external subtitles. Important steps in solving this problem are detection, localization, and binding of these subtitles to frames of the video stream. This paper proposes a method for detection and localization of embedded subtitles in video stream. The method is based on the search for static regions in the frames of the video stream and subsequent analysis of the connected areas inside them. Based on the results of this analysis, we determine whether a region belongs to the area of subtitles and localize text strings in the detected subtitles. The proposed method does not require large computational costs and can work in real time.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blecic, David Taniar, Bernady O. Apduhan, Ana Maria A.C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca
PublisherSpringer Nature
Pages119-128
Number of pages10
ISBN (Print)9783030588168
DOIs
StatePublished - 2020
Event20th International Conference on Computational Science and Its Applications, ICCSA 2020 - Cagliari, Italy
Duration: 1 Jul 20204 Jul 2020
http://iccsa.org/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12254 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science and Its Applications, ICCSA 2020
Abbreviated titleICCSA 2020
Country/TerritoryItaly
CityCagliari
Period1/07/204/07/20
Internet address

    Research areas

  • Embedded subtitles, Image segmentation, Subtitles localization

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 86276349