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

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.

Authors

Institutions

Publication Details

Journal
Advances in Artificial Intelligence Research
Published
2024-08-30
DOI
https://doi.org/10.54569/aair.1401234
Citations
2
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.64
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Mehmet Hilmi Emel, Murat Terzioğlu, Ramazan Özkan
2 citations
Advances in Artificial Intelligence Research
Vehicle License Plate Recognition
0.64
article

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

Mehmet Hilmi Emel, Murat Terzioğlu, Ramazan Özkan
article en
2 citations

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.

Advances in Artificial Intelligence ResearchVol. 4(1)
Haliç University (TR), Badan Pengkajian dan Penerapan Teknologi (ID)
Openalex Percentile: Top 27%
Vehicle License Plate Recognition
0.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.