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Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Handwriting Recognition System Using OCR

Authors: Mrs Apoora Mane; Miss Anushree Kalloli; Miss Ishwari Kamble; Mr Amol Kote; Mr Tejas Padwal;

Handwriting Recognition System Using OCR

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.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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