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ICDAR 2021 Soutěž v segmentaci historických map
- 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/
- Subjects :
- FOS: Computer and information sciences
Computer science
map vectorization
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
02 engineering and technology
Task (project management)
Hough transform
law.invention
03 medical and health sciences
law
0202 electrical engineering, electronic engineering, information engineering
Historická mapa
Segmentation
030304 developmental biology
soutěž
0303 health sciences
historical maps
business.industry
Intersection (set theory)
Template matching
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Pattern recognition
Pipeline (software)
vektorizace mapy
Line (geometry)
[SDE]Environmental Sciences
020201 artificial intelligence & image processing
Artificial intelligence
Scale (map)
business
competition
Subjects
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