ICDAR 2024 Competition on Historical Map Text Detection, Recognition, and Linking

Zekun Li, Yijun Lin, Yao Yi Chiang, Jerod Weinman, Solenn Tual, Joseph Chazalon, Julien Perret, Bertrand Duménieu, Nathalie Abadie

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

Abstract

Text on digitized historical maps contains valuable information, e.g., providing georeferenced political and cultural context. The goal of the ICDAR 2024 MapText Competition is to benchmark methods that automatically extract textual content on historical maps (e.g., place names) and connect words to form location phrases. The competition features two primary tasks—text detection and end-to-end text recognition—each with a secondary task of linking words into phrase blocks. Submissions are evaluated on two data sets: 1) David Rumsey Historical Map Collection which contains 936 map images covering 80 regions and 183 distinct publication years (from 1623 to 2012); 2) French Land Registers (created during the 19th century) which contains 145 map images of 50 French cities and towns. The competition received 44 submissions among all tasks. This report presents the motivation for the competition, the tasks, the evaluation metrics, and the submission analysis.

Original languageEnglish (US)
Title of host publicationDocument Analysis and Recognition - ICDAR 2024 - 18th International Conference, Proceedings
EditorsElisa H. Barney Smith, Marcus Liwicki, Liangrui Peng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages363-380
Number of pages18
ISBN (Print)9783031705519
DOIs
StatePublished - 2024
Event18th International Conference on Document Analysis and Recognition, ICDAR 2024 - Athens, Greece
Duration: Aug 30 2024Sep 4 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14809 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Document Analysis and Recognition, ICDAR 2024
Country/TerritoryGreece
CityAthens
Period8/30/249/4/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

  • Historical maps
  • Text detection
  • Text recognition

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