Khayyam Offline Persian Handwriting Dataset

TL;DR

The Khayyam dataset provides a large, diverse collection of Persian handwriting samples, including rare words, to facilitate machine learning research in Persian handwriting recognition.

Contribution

It introduces a comprehensive, publicly available Persian handwriting dataset with extensive samples, including rare words, for improved recognition research.

Findings

Machine learning algorithms trained on the dataset achieve promising results.

The dataset covers words, letters, and digits with samples from 400 writers.

It demonstrates the dataset's applicability for training and evaluating handwriting recognition models.

Abstract

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.