ICDAR 2021 Competition on Historical Map Segmentation

Authors

Joseph Chazalon, Edwin Carlinet, Yizi Chen, Julien Perret, Bertrand Duménieu, Clément Mallet, Thierry Géraud, Vincent Nguyen, Nam Nguyen, Josef Baloun, Ladislav Lenc, Pavel Král

Where

Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21)

Place

Lausanne, Switzerland

Type

inproceedings

Publisher

Springer, Cham

Projects

Olena

Keywords

Image

Date

2021-05-17

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 transformcandidate 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 https://icdar21-mapseg.github.io/.

Documents

• Paper

Bibtex (lrde.bib)

@InProceedings{	  chazalon.21.icdar.2,
  title		= {{ICDAR} 2021 Competition on Historical Map Segmentation},
  author	= {Joseph Chazalon and Edwin Carlinet and Yizi Chen and
		  Julien Perret and Bertrand Dum\'enieu and Cl\'ement Mallet
		  and Thierry G\'eraud and Vincent Nguyen and Nam Nguyen and
		  Josef Baloun and Ladislav Lenc and Pavel Kr\'al},
  booktitle	= {Proceedings of the 16th International Conference on
		  Document Analysis and Recognition (ICDAR'21)},
  year		= {2021},
  month		= sep,
  pages		= {693--707},
  series	= {Lecture Notes in Computer Science},
  publisher	= {Springer, Cham},
  volume	= {12824},
  address	= {Lausanne, Switzerland},
  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/}.},
  doi		= {10.1007/978-3-030-86337-1_46}
}