# DDI-100: Dataset for Text Detection and Recognition

arXiv: https://arxiv.org/abs/1912.11658 · HTML: https://mlsanity.com/paper/1912.11658/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Dec 2019.

## Built on by (most cited first, 6 of 6)

- [Detection Masking for Improved OCR on Noisy Documents](https://mlsanity.com/paper/2205.08257/) (2022)
- [Iranis: A Large-scale Dataset of Farsi License Plate Characters](https://mlsanity.com/paper/2101.00295/) (2021)
- [BusiNet -- a Light and Fast Text Detection Network for Business Documents](https://mlsanity.com/paper/2207.01220/) (2022)
- [PEaCE: A Chemistry-Oriented Dataset for Optical Character Recognition on Scientific Documents](https://mlsanity.com/paper/2403.15724/) (2024)
- [Text Change Detection in Multilingual Documents Using Image Comparison](https://mlsanity.com/paper/2412.04137/) (2024)
- [ShabbyPages: A Reproducible Document Denoising and Binarization Dataset](https://mlsanity.com/paper/2303.09339/) (2023)

## Abstract (arXiv)

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.