ICDAR 2021 Competition on Historical Map Segmentation
This work addresses the challenge of digitizing and analyzing historical maps for researchers and archivists, but it is incremental as it builds on existing segmentation and detection techniques in a competition setting.
The paper presents the results of the ICDAR 2021 Competition on Historical Map Segmentation, which tackled the problem of segmenting historical maps of Paris into building blocks, map content, and geo-referencing lines, with winning methods achieving top performance in tasks evaluated on large images and complex map sheets.
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/}.