Viral transcript alignment

Gil Sadeh, Lior Wolf, Tal Hassner, Nachum Dershowitz, Daniel Stokl Ben-Ezra

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

Abstract

We present an end-to-end system for aligning transcript letters to their coordinates in a manuscript image. An intuitive GUI and an automatic line detection method enable the user to perform an exact alignment of parts of document pages. In order to bridge large regions in between annotation, and augment the manual effort, the system employs an optical-flow engine for directly matching at the pixel level the image of a line of a historical text with a synthetic image created from the transcript's matching line. Meanwhile, by accumulating aligned letters, and performing letter spotting, the system is able to bootstrap a rapid semi-automatic transcription of the remaining text. Thus, the amount of manual work is greatly diminished and the transcript alignment task becomes practical regardless of the corpus size.

Original languageEnglish
Title of host publication13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015 - Conference Proceedings
PublisherIEEE Computer Society
Pages711-715
Number of pages5
ISBN (Electronic)9781479918058
DOIs
StatePublished - 20 Nov 2015
Event13th International Conference on Document Analysis and Recognition, ICDAR 2015 - Nancy, France
Duration: 23 Aug 201526 Aug 2015

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2015-November
ISSN (Print)1520-5363

Conference

Conference13th International Conference on Document Analysis and Recognition, ICDAR 2015
Country/TerritoryFrance
CityNancy
Period23/08/1526/08/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

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