The paper presents a local traditional OCR pipeline that can be iteratively fine‑tuned on both layout and appearance levels of complex historical Sanskrit manuscripts. By adapting to the specific manuscript distribution, the pipeline reduces human annotation effort and improves transcription accuracy across subsequent pages. The authors apply this method to three manuscripts, release a dataset with detailed layout and Unicode annotations in PAGE‑XML format, and benchmark the pipeline against leading multimodal large language models.
By Kartik Chincholikar, Kaushik Gopalan, Mihir Hasabnis
The paper introduces Synth-JDoc, a synthetic Japanese document image dataset created by rendering text with HTML and CSS to produce multi‑column layouts that include both vertical and horizontal writing styles. Images generated by text‑to‑image models are embedded to enhance visual realism, and noise and degradation filters are applied to improve robustness. Experiments show that fine‑tuning Large Vision Language Models on Synth‑JDoc yields superior performance on reading vertically written Japanese text compared to prior synthetic datasets.
By Keito Sasagawa, Shuhei Kurita, Daisuke Kawahara
arXiv:2607. 20385v1 Announce Type: cross Abstract: Optical Character Recognition (OCR) for Persian remains substantially less mature than for Latin-script languages despite Persian being spoken by more than 110 million people across multiple countries.
By Pouria Mahdi, Haq Nawaz Malik
arXiv:2502. 20295v3 Announce Type: replace-cross Abstract: Handwriting text recognition (HTR) remains a challenging task.
By Benjamin Gutteridge, Matthew Thomas Jackson, Toni Kukurin, Xiaowen Dong
UniLipi is a unified multi‑script OCR model trained on 13 Indic scripts to recognize handwritten manuscripts under challenging conditions such as varied line geometry, length, and interruptions by non‑textual elements. It uses script‑aware synthetic data generation to perform well even with limited real annotated data. The model also predicts script identity and per‑line character counts, aiding manuscript cataloging, and its representations transfer to contemporary Indic handwriting and several non‑Indic scripts.
By Tathagata Ghosh, Sai Madhusudan Gunda, Simran Singh Sandral, Ravi Kiran Sarvadevabhatla
arXiv:2610.09439v1 Announce Type: new
Abstract: Ancient script image restoration is a fundamental problem in computer vision, as it directly affects the reliable analysis and interpretation of histor...
By Jaidev Sanjay Khalane, Akbar Ali, V. N. Prabhakar, Shanmuganathan Raman