Handwriting Recognition System Using OCR

This project presents an Image Text Recognition and Translation System that extracts text from images and converts it into editable and translatable digital content. The system uses image processing techniques to enhance image quality and improve text detection accuracy. By integrating Tesseract OCR, the application efficiently recognizes printed and partially handwritten text from images. After extraction, the recognized text is translated into different languages using an integrated translation module, making the system useful for multilingual communication. Additionally, the system stores the original and translated text in a database, enabling users to maintain a history of their data for future reference. This project aims to reduce manual effort, improve productivity, and provide a user-friendly solution for text extraction and translation. It can be applied in areas such as document digitization, education, and travel assistance. Future improvements may include enhanced handwriting recognition, voice output, and mobile application support.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-01
DOI
https://doi.org/10.5281/zenodo.19254810
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Handwriting Recognition System Using OCR

Miss Ishwari Kamble, Mr Amol Kote, Miss Anushree Kalloli, Mrs Apoora Mane et al.
Zenodo (CERN European Organization for Nuclear Research)
Handwritten Text Recognition Techniques
article

Handwriting Recognition System Using OCR

Miss Ishwari Kamble, Mr Amol Kote, Miss Anushree Kalloli, Mrs Apoora Mane, Mr Tejas Padwal
article en

Abstract

This project presents an Image Text Recognition and Translation System that extracts text from images and converts it into editable and translatable digital content. The system uses image processing techniques to enhance image quality and improve text detection accuracy. By integrating Tesseract OCR, the application efficiently recognizes printed and partially handwritten text from images. After extraction, the recognized text is translated into different languages using an integrated translation module, making the system useful for multilingual communication. Additionally, the system stores the original and translated text in a database, enabling users to maintain a history of their data for future reference. This project aims to reduce manual effort, improve productivity, and provide a user-friendly solution for text extraction and translation. It can be applied in areas such as document digitization, education, and travel assistance. Future improvements may include enhanced handwriting recognition, voice output, and mobile application support.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 5%
Handwritten Text Recognition Techniques
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