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Updated: Jul 3, 2025

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Tamil handwritten palm leaf manuscript dataset (THPLMD).

I Jailingeswari1, S Gopinathan1

  • 1Department of Computer Science, University of Madras, Chennai, India.

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This study presents a new dataset of 262 deteriorated Tamil palm leaf manuscripts, crucial for advancing machine learning and artificial intelligence research. The dataset aids in preserving and analyzing these historically significant texts.

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Area of Science:

  • Digital Humanities
  • Computer Vision
  • Manuscriptology

Background:

  • Palm leaf manuscripts are vital historical records but often exist in deteriorated states.
  • Challenges in research include physical degradation like cracks, discoloration, and insect damage.
  • Digitization and analysis of these manuscripts are essential for preservation and study.

Purpose of the Study:

  • To create a high-quality, accessible dataset of deteriorated Tamil palm leaf manuscripts.
  • To facilitate research in machine learning, artificial intelligence, and related fields.
  • To aid in the preservation and study of historical Tamil texts.

Main Methods:

  • Collected 262 deteriorated Tamil palm leaf manuscript samples ('Naladiyar', 'Tholkappiyam', 'Thirikadugam').
  • Captured high-quality images using a Nikon camera.
  • Pre-enhanced images using editing software and applied Otsu thresholding for binarization.

Main Results:

  • Developed a readily accessible dataset of binarized manuscript images.
  • The dataset comprises samples focusing on mortal health, discipline, and Tamil grammar.
  • The process, though time-consuming, yields valuable ground images for AI applications.

Conclusions:

  • The created dataset is a significant contribution to the field of digital humanities and AI.
  • This resource will accelerate research in machine learning, deep learning, and artificial neural networks for manuscript analysis.
  • Enables further computational study and preservation of endangered Tamil literary heritage.