A user-centered segmentation method for complex historical manuscripts based on document graphs

Garz, Angelika (Document, Image, and Voice Analysis Research Group, Department of Informatics, University of Fribourg, Fribourg, Switzerland) ; Seuret, Mathias (Document, Image, and Voice Analysis Research Group, Department of Informatics, University of Fribourg, Fribourg, Switzerland) ; Fischer, Andreas (School of Engineering and Architecture (HEIA-FR), HES-SO // University of Applied Sciences Western Switzerland ; Document, Image, and Voice Analysis Research Group, Department of Informatics, University of Fribourg, Fribourg, Switzerland) ; Ingold, Rolf (Document, Image, and Voice Analysis Research Group, Department of Informatics, University of Fribourg, Fribourg, Switzerland)

In historical manuscripts, humans can detect handwritten words, lines, and decorations with lightness even if they do not know the language or the script. Yet for automatic processing this task has proven elusive, especially in the case of handwritten documents with complex layouts, which is why semiautomatic methods that integrate the human user into the process are needed. In this paper, we introduce a user-centered segmentation method based on document graphs and scribbling interaction. The graphs capture a sparse representation of the document's structure that can then be edited by the user with a stylus on a touch-sensitive screen. We evaluate the proposed method on a newly introduced database of historical manuscripts with complex layout and demonstrate, first, that the document graphs are already close to the desired segmentation and, second, that scribbling allows a natural and efficient interaction.


Keywords:
Article Type:
scientifique
Faculty:
Ingénierie et Architecture
School:
HEIA-FR
Institute:
iCoSys - Institut des systèmes complexes
Date:
2017-04
Pagination:
13 p.
Published in:
IEEE Transactions on Human-Machine Systems
Numeration (vol. no.):
2017, vol. 47, no. 2, pp- 181-193
DOI:
ISSN:
2168-2291
Appears in Collection:

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 Record created 2020-10-13, last modified 2020-10-27

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