Nowadays document analysis and recognition remain challenging tasks. However, only a few datasets designed for text detection (TD) and optical character recognition (OCR) problems exist. In this paper we present Distorted Document Images dataset (DDI-100) and demonstrate its usefulness in a wide range of document analysis problems. DDI-100 dataset is a synthetic dataset based on 7000 real unique document pages and consists of more than 100000 augmented images. Ground truth comprises text and stamp masks, text and characters bounding boxes with relevant annotations. Validation of DDI-100 dataset was conducted using several TD and OCR models that show high-quality performance on real data.
@article{arxiv.1912.11658,
title = {DDI-100: Dataset for Text Detection and Recognition},
author = {Ilia Zharikov and Filipp Nikitin and Ilia Vasiliev and Vladimir Dokholyan},
journal= {arXiv preprint arXiv:1912.11658},
year = {2021}
}
Comments
Accepted by CCVPR 2019. Dataset is available here: https://github.com/machine-intelligence-laboratory/DDI-100