Abstract: "Text Extractor OCR-NER Form Filling Automation" is an innovative software solution designed to streamline the process of extracting text from documents, performing Optical Character Recognition (OCR) and Named Entity Recognition (NER) tasks, and automating form filling tasks. This project aims to enhance efficiency and accuracy in data extraction and form completion processes across various industries. The system leverages OCR technology to extract text from scanned documents, images enabling users to digitize and analyze textual content effectively. Additionally, it employs Named Entity Recognition techniques to identify and categorize specific entities such as names, dates, locations, and organizations within the extracted text. Key features of the application include a user-friendly interface for uploading and processing documents, robust OCR and NER algorithms for accurate text extraction and entity recognition, and automation capabilities for filling predefined form fields with extracted information. Through this project, users can significantly reduce manual data entry efforts, minimize errors associated with manual transcription, and expedite the processing of documents and forms.
Keywords: Text Extractor, OCR-NER, Form Filling, Automation, Software Solution, Optical Character Recognition, Named Entity Recognition, Data Extraction, Document Management, Data Processing.
Cite:
Prajwal U, Shodhan Kumar Shetty, Sujan J Acharya, Swapnil Shetty, Maryjo M George, "TEXT EXTRACTOR: OCR-NER FORM FILLING AUTOMATION", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13347.
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DOI:
10.17148/IJARCCE.2024.13347
