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| Main Authors: | , , , , |
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| Format: | Recurso digital |
| Jezik: | angleščina |
| Izdano: |
Zenodo
2026
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| Online dostop: | https://doi.org/10.5281/zenodo.19254811 |
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| _version_ | 1866901220417863680 |
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| author | Mrs Apoora Mane Miss Anushree Kalloli Miss Ishwari Kamble Mr Amol Kote Mr Tejas Padwal |
| author_facet | Mrs Apoora Mane Miss Anushree Kalloli Miss Ishwari Kamble Mr Amol Kote Mr Tejas Padwal |
| contents | 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. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19254811 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Handwriting Recognition System Using OCR Mrs Apoora Mane Miss Anushree Kalloli Miss Ishwari Kamble Mr Amol Kote Mr Tejas Padwal 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. |
| title | Handwriting Recognition System Using OCR |
| url | https://doi.org/10.5281/zenodo.19254811 |