Software Open Access

Visual-Pattern Detector v1.3 (VPD1.3)

Hussein Mohammed

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.

What is new?

  • Better and more intuitive design
  • Bugs fixes

Main usage:

The main goal of this software tool is to automatically recognise and allocate visual patterns (such as words, drawings and seals) in digitised manuscripts. The recall-precision balance of detected patterns can be controlled visually, and the detected patterns can be saved as annotations on the original images or as cropped images depending on the needs of users.

Acknowledgement:

The development of this software was sponsored by the Cluster of Excellence 2176 ‘Understanding Written Artefacts’, generously funded by the German Research Foundation (DFG), within the scope of the work conducted at Centre for the Study of Manuscript Cultures (CSMC).

I would like to thank the following colleagues for testing this software tool and validating the results: Dr. Giovanni Ciotti (CSMC), Dr. Volker Märgner (Technische Universität Braunschweig), Dr. Agnieszka Helman-Wazny (CSMC), Dr. Isabelle Marthot-Santaniello (Universität Basel).

Files (86.6 MB)
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ReadMe.txt
md5:ded366353007758624b8a35c55f898ee 		625 Bytes Download
VPD1p3_BestWorst.png
md5:092a3e6317c4b3bb45db0ac6331fd0d5 		187.1 kB Download
Win-x64.zip
md5:753895f3c19964f9b0ba55fbfaae881b 		86.4 MB Download
  • 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
  • Mohammed, H., Märgner, V., & Ciotti, G. (2021). Learning-free pattern detection for manuscript research. International Journal on Document Analysis and Recognition (IJDAR), 1-13.
Publication date:
May 26, 2021
DOI:
10.25592/uhhfdm.9186

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Keyword(s):
Pattern Detection Document Analysis Pattern Recognition Computer Vision
Communities:
License (for files):
Creative Commons Attribution 4.0 International

Versions

Version 1.3.0 10.25592/uhhfdm.9186 May 26, 2021
Version 1.0.0 10.25592/uhhfdm.8833 Feb 22, 2021
Cite all versions? You can cite all versions by using the DOI 10.25592/uhhfdm.8832. This DOI represents all versions, and will always resolve to the latest one.

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