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Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions

Year: 2024

Type: article

Abstract: In the realm of contemporary document processing, the challenge of extracting crucial information from diverse invoices necessitates innovative solutions. This article presents a comprehensive three-step methodology to address the complexity of date extraction from invoices. Leveraging LabelStudio, Python, and OpenCV, we constitute a dataset and train a custom object detection model using Ultralytics YOLOv8. Optical Character Recognition (OCR) provides us to convert the image data to string data that is enable to be processed. Regular expressions refine the extracted text, achieving precise date formats. The developed system significantly enhance the time efficiency, marking a noteworthy advancement in date extraction from invoices.

Source: Advances in Artificial Intelligence Research

DOI: 10.54569/aair.1401234

Authors: Mehmet Hilmi Emel, Murat Terzioğlu, Ramazan Özkan

Institution: Haliç University

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4402054544

FWCI: 0.719

Cites: 6

Cited by: 5

Related to: 10