Publication Details

Brno Mobile OCR Dataset

KIŠŠ Martin, HRADIŠ Michal and KODYM Oldřich. Brno Mobile OCR Dataset. In: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. Sydney: Institute of Electrical and Electronics Engineers, 2020, pp. 1352-1357. ISBN 978-1-7281-3015-6. Available from:
Czech title
Brno Mobilní OCR Dataset
conference paper
Kišš Martin, Ing. (DCGM FIT BUT)
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT)
Kodym Oldřich, Ing., Ph.D. (DCGM FIT BUT)

OCR, CTC, mobile, dataset


We introduce the Brno Mobile OCR Dataset (B-MOD) for document Optical Character Recognition from low-quality images captured by handheld mobile devices. While OCR of high-quality scanned documents is a mature field where many commercial tools are available, and large datasets of text in the wild exist, no existing datasets can be used to develop and test document OCR methods robust to non-uniform lighting, image blur, strong noise, built-in denoising, sharpening, compression and other artifacts present in many photographs from mobile devices.

This dataset contains 2 113 unique pages from random scientific papers, which were photographed by multiple people using 23 different mobile devices. The resulting 19 728 photographs of various visual quality are accompanied by precise positions and text annotations of 500k text lines. We further provide an evaluation methodology, including an evaluation server and a testset with non-public annotations.

We provide a state-of-the-art text recognition baseline build on convolutional and recurrent neural networks trained with Connectionist Temporal Classification loss. This baseline achieves 2 %, 23 % and 73 % word error rates on easy, medium and hard parts of the dataset, respectively, confirming that the dataset is challenging.

The presented dataset will enable future development and evaluation of document analysis for low-quality images. It is primarily intended for line-level text recognition, and can be further used for line localization, layout analysis, image restoration and text binarization.

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
International Conference on Document Analysis and Recognition, Sydney, Australia, AU
Institute of Electrical and Electronics Engineers
Sydney, AU
EID Scopus
   author = "Martin Ki\v{s}\v{s} and Michal Hradi\v{s} and Old\v{r}ich Kodym",
   title = "Brno Mobile OCR Dataset",
   pages = "1352--1357",
   booktitle = "Proceedings of the International Conference on Document Analysis and Recognition, ICDAR",
   year = 2020,
   location = "Sydney, AU",
   publisher = "Institute of Electrical and Electronics Engineers",
   ISBN = "978-1-7281-3015-6",
   doi = "10.1109/ICDAR.2019.00218",
   language = "english",
   url = ""
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