Software Open Access

Handwriting Analysis Tool v3.5 (HAT3.5)

Mohammed, Hussein

What is new in this version?

  • Better and more intuitive design.
  • Progress indicator is now provided.
  • Upload size-limit is increased.
  • Analysing the images is sped up.
  • Several bug fixes.

This software tool has been developed by Dr. Hussein Mohammed as a part of sub-project RFA05: Pattern Recognition in 2D Data from Digitised Images and Advanced Aquisition Techniques.

The main goal of HAT is to analyse handwriting styles of different scribes and sort them according to their similarity to specific (possibly unknown) handwriting styles. A similarity score will be produced for each of the different handwriting styles (scribes) so that the user can have a relative comparison between the similarities of handwriting styles with respect to specific handwriting styles (possibly from unknown scribes).

The research for this software was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany´s Excellence Strategy – EXC 2176 ‘Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures’, project no. 390893796. The research was conducted within the scope of the Centre for the Study of Manuscript Cultures (CSMC) at Universität Hamburg.

Files (83.3 MB)
Name Size
HAT3p5.jpg
md5:3ae8cd0f6abb205d2b884b9a10196a3e
64.7 kB Download
ReadMe.txt
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561 Bytes Download
Win_x64.zip
md5:9fe9e3e19d74a2c997d9dddff5245712
83.2 MB Download
  • H. Mohammed, V. Märgner and H. S. Stiehl, "Writer Identification for Historical Manuscripts: Analysis and Optimisation of a Classifier as an Easy-to-Use Tool for Scholars from the Humanities," 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), Niagara Falls, NY, 2018, pp. 534-539.
  • Mohammed, H., Helman-Wazny, A., Colini, C., Beyer, W., Bosch, S. (2022). Pattern Analysis Software Tools (PAST) for Written Artefacts. In: Uchida, S., Barney, E., Eglin, V. (eds) Document Analysis Systems. DAS 2022. Lecture Notes in Computer Science, vol 13237. Springer, Cham. https://doi.org/10.1007/978-3-031-06555-2_15

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