Handwritten Notes Digitization and Multilingual Summarization Using OCR and Generative AI

Suchetha N V; Anisha Upadhayaya H S; Anushree U Rao; H N Swati; Mallana  Gowda G S

doi:10.55524/ijircst.2026.14.1.2

Abstract

This research proposes a fully client-side system for digitising and summarising handwritten notes that integrate optical character recognition (OCR) with advanced natural language generation models. Initial experimentation with a Convolutional Neural Network (CNN)– based handwritten character recognition system revealed significant challenges, including low recognition accuracy, strong dependence on dataset quality, and poor generalisation across diverse handwriting styles. A subsequent implementation using Gemini 2.5 Pro provided high-quality English summaries but failed to deliver equivalent performance for multilingual academic content. To overcome these issues, this study adopts a hybrid methodology combining Tesseract.js OCR for multilingual text extraction with Gemini 2.5 Flash for fast, context-aware, and language-flexible summarization. The system is able to take handwritten notes, convert them into clear and readable text, and produce well-structured academic summaries across different subjects and languages. Our tests show that it works reliably, adapts well to multiple languages, and is easy to use, making it a strong and practical tool for educational digitization.

Keywords

Handwritten Note Digitization, OCR, CNN, NLP, Multilingual Processing, Summarization, Deep Learning

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Cites this article as

S. N. V, A. U. H. S, A. U. Rao, H. N. Swati, M. . G. G. S, "Handwritten Notes Digitization and Multilingual Summarization Using OCR and Generative AI", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-14, Issue-1, Page No-9-16, 2026. Available from: https://doi.org/10.55524/ijircst.2026.14.1.2

Corresponding Author

Suchetha N V

Associate Professor, Department of Computer Science & Engineering, Sri Dharmasthala Manjunatheshwara Institute of Technology, Ujire, Karnataka, India

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