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ICDAR 2021 Soutěž v segmentaci historických map

Authors :
Julien Perret
Vincent Nguyen
Ladislav Lenc
Yizi Chen
Josef Baloun
Pavel Král
Joseph Chazalon
Nam Nguyen
Bertrand Duménieu
Edwin Carlinet
Clément Mallet
Thierry Géraud
Laboratoire de Recherche et de Développement de l'EPITA (LRDE)
Ecole Pour l'Informatique et les Techniques Avancées (EPITA)
Laboratoire sciences et technologies de l'information géographique (LaSTIG)
Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG)
Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel
École des hautes études en sciences sociales (EHESS)
Laboratoire Informatique, Image et Interaction - EA 2118 (L3I)
Université de La Rochelle (ULR)
Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS)
Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-École Centrale de Lyon (ECL)
Université de Lyon-Université Lumière - Lyon 2 (UL2)
University of West Bohemia [Plzeň ]
Springer, Cham
Source :
Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21), 16th International Conference on Document Analysis and Recognition (ICDAR'21), 16th International Conference on Document Analysis and Recognition (ICDAR'21), Sep 2021, Lausanne, Switzerland. pp.693-707, ⟨10.1007/978-3-030-86337-1_46⟩, Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030863364, ICDAR (4)
Publication Year :
2021
Publisher :
Springer, 2021.

Abstract

This paper presents the final results of the ICDAR 2021 Competition on Historical Map Segmentation (MapSeg), encouraging research on a series of historical atlases of Paris, France, drawn at 1/5000 scale between 1894 and 1937. The competition featured three tasks, awarded separately. Task~1 consists in detecting building blocks and was won by the L3IRIS team using a DenseNet-121 network trained in a weakly supervised fashion. This task is evaluated on 3 large images containing hundreds of shapes to detect. Task~2 consists in segmenting map content from the larger map sheet, and was won by the UWB team using a U-Net-like FCN combined with a binarization method to increase detection edge accuracy. Task~3 consists in locating intersection points of geo-referencing lines, and was also won by the UWB team who used a dedicated pipeline combining binarization, line detection with Hough transform, candidate filtering, and template matching for intersection refinement. Tasks~2 and~3 are evaluated on 95 map sheets with complex content. Dataset, evaluation tools and results are available under permissive licensing at \url{https://icdar21-mapseg.github.io/}.<br />Selected as one of the official competitions for the 16th International Conference on Document Analysis and Recognition (ICDAR 2021), September 5-10, 2021, Lausanne, Switzerland (https://icdar2021.org/). Extra material available at https://icdar21-mapseg.github.io/

Details

Language :
English
ISBN :
978-3-030-86336-4
ISBNs :
9783030863364
Database :
OpenAIRE
Journal :
Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21), 16th International Conference on Document Analysis and Recognition (ICDAR'21), 16th International Conference on Document Analysis and Recognition (ICDAR'21), Sep 2021, Lausanne, Switzerland. pp.693-707, ⟨10.1007/978-3-030-86337-1_46⟩, Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030863364, ICDAR (4)
Accession number :
edsair.doi.dedup.....83e714c32b620051e1f9dbf3c992e4f7