# Khayyam Offline Persian Handwriting Dataset

arXiv: https://arxiv.org/abs/2406.01025 · HTML: https://mlsanity.com/paper/2406.01025/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 37 references that are in the map.
- First posted on arXiv 3 Jun 2024.

## Builds on (most cited first, 3 of 3)

- [Persian Handwritten Digit, Character and Word Recognition Using Deep Learning](https://mlsanity.com/paper/2010.12880/) (2020)
- [Deep Template Matching for Offline Handwritten Chinese Character Recognition](https://mlsanity.com/paper/1811.06347/) (2018)
- [Does color modalities affect handwriting recognition? An empirical study on Persian handwritings using convolutional neural networks](https://mlsanity.com/paper/2307.12150/) (2023)

## Built on by (most cited first, 1 of 1)

- [HPMD: A Historical Persian Manuscript Dataset for Word Spotting with Line-Level Annotation](https://mlsanity.com/paper/2609.34490/) (2026)

## Abstract (arXiv)

Handwriting analysis is still an important application in machine learning. A basic requirement for any handwriting recognition application is the availability of comprehensive datasets. Standard labelled datasets play a significant role in training and evaluating learning algorithms. In this paper, we present the Khayyam dataset as another large unconstrained handwriting dataset for elements (words, sentences, letters, digits) of the Persian language. We intentionally concentrated on collecting Persian word samples which are rare in the currently available datasets. Khayyam's dataset contains 44000 words, 60000 letters, and 6000 digits. Moreover, the forms were filled out by 400 native Persian writers. To show the applicability of the dataset, machine learning algorithms are trained on the digits, letters, and word data and results are reported. This dataset is available for research and academic use.