Dataset Viewer
Auto-converted to Parquet
The dataset viewer is not available for this split.
Rows from parquet row groups are too big to be read: 556.41 MiB (max=286.10 MiB)
Error code:   TooBigContentError

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

ICDAR 2015 HTRtS Competition Dataset

Dataset Description

The ICDAR 2015 Competition HTRtS dataset was used for the "Handwritten Text Recognition on the tranScriptorium Dataset" competition held at the International Conference on Document Analysis and Recognition (ICDAR) in 2015.

The dataset images are drawn from the English "Bentham collection", originally used in the European-funded TRAN SCRIPTORIUM project.

The data features significant difficulties, including:

  • Variations in image quality.
  • Multiple writing styles (written by several different hands).
  • Presence of crossed-out text.

This competition dataset was noted as being more challenging than the previous edition.

Dataset Creation

Source Data

The handwritten images are sourced from the Bentham collection used in the TRAN SCRIPTORIUM project.

Creators

The creators of this competition dataset are: J.A. Sánchez, A.H. Toselli, V. Romero, and E. Vidal. All are affiliated with the Pattern Recognition and Human Language Technologies Research Center at Universitat Politècnica de València.

Funding

The dataset is connected to the European Commission's TRAN SCRIPTORIUM (600707) project.

License

The dataset is licensed under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license.

Citation

When using this dataset, please cite the original Zenodo record, which references the associated competition paper:

@inproceedings{SanchezToselliRomeroVidal2017,
  author    = {S\'{a}nchez, J. A. and Toselli, A. H. and Romero, V. and Vidal, E.},
  title     = {{ICDAR 2015 Competition HTRtS: Handwritten Text Recognition on the tranScriptorium Dataset}},
  publisher = {Zenodo},
  year      = {2017},
  doi       = {10.5281/zenodo.248733},
  url       = {[https://zenodo.org/records/248733](https://zenodo.org/records/248733)}
}
Downloads last month
65