CT-OCR-2022 (scroll001)

CT-OCR-2022 dataset

CT-OCR-2022 dataset contains optically scanned images for source paper document, 400 X-ray projections, 2687 CT-reconstructed cross-sections and  segmentation markups for 6 model objects.

Description of the data for each model object is presented in the table.

Files
Data description

2022-ICMV-CT-OCR.[package].png
sample projection and slice visualization

[package].proj_src/proj_s_.log
X-ray measurement log file

[package].proj_src/*.tif
preprocessed projections before rotation axe correction

2022-ICMV-CT-OCR.[package].png
package single projection and slice vizualization

[package].proj_src/*.tif
preprocessed projections before rotation axe correction

[package].proj_norm/proj_s_.log
X-ray measurement and geometry correction log file

[package].proj_norm/*.tif
preprocessed projections after rotation axe correction

[package].rec_XXXX/metadata.json
reconstruction metadata

[package].rec_XXXX/*.tif
CT-reconstructed volume, slices with size XXXX×XXXX

[package].seg_XXXX/*.tif.seg.png
segmentation markup

[package].blank.png
sample croped from pdf

[package].scan.png
sample croped from scanned image

Due to the large amount of data, folders were packed into multi-volume zip-archives. Dataset published in Zenodo service in several linked repositories.

scroll01 - 10.5281/zenodo.7123495scroll02 - 10.5281/zenodo.7157600scroll03 - 10.5281/zenodo.7157610scroll04 - 10.5281/zenodo.7161350folded01 - 10.5281/zenodo.7162001, 10.5281/zenodo.7164152folded02 - 10.5281/zenodo.7267141, 10.5281/zenodo.7272064

Any questions, complaints, etc. can be directed to: [e-mail] (Dmitry Polevoy)

Share and Cite:

D. V. Polevoy, P. A. Kulagin, A. S. Ingacheva, Zh. V. Soldatova, M. V. Chukalina, D. P. Nikolaev, V. V. Arlazarov, "From tomographic reconstruction to automatic text recognition: the next frontier task for the artificial intelligence," Proc. SPIE 12701, Fifteenth International Conference on Machine Vision (ICMV 2022), 127010P (7 June 2023); https://doi.org/10.1117/12.2680132

in BibTex format:

@inproceedings{10.1117/12.2680132,author = {D. V. Polevoy and P. A. Kulagin and A. S. Ingacheva and Zh. V. Soldatova and M. V. Chukalina and D. P. Nikolaev and V. V. Arlazarov},title = {{From tomographic reconstruction to automatic text recognition: the next frontier task for the artificial intelligence}},volume = {12701},booktitle = {Fifteenth International Conference on Machine Vision (ICMV 2022)},editor = {Wolfgang Osten and Dmitry P. Nikolaev and Jianhong (Jessica) Zhou},organization = {International Society for Optics and Photonics},publisher = {SPIE},pages = {127010P},keywords = {virtual unrolling, virtual unwrapping, digital unfolding, computational flattening, computed tomography, non-destructive analysis, open dataset},year = {2023},doi = {10.1117/12.2680132},URL = {https://doi.org/10.1117/12.2680132}}

See also

P. A. Kulagin, D. V. Polevoy, M. V. Chukalina, D. P. Nikolaev and V. V. Arlazarov, “Fully automatic virtual unwrapping method for documents imaged by X-ray tomography,” Proc. ICDAR 2024, to be published.

https://github.com/SmartEngines/virtual-unwrapping-article-code