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

Yıl 2024, , 10 - 17, 30.08.2024

Mehmet Hilmi Emel , Murat Terzioğlu , Ramazan Özkan

https://doi.org/10.54569/aair.1401234

Öz

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.

Anahtar Kelimeler

Custom Object Detection, OCR, Invoice Processing, YOLOv8

Kaynakça

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