Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

AI-Enhanced Optical Character Recognition for Country-Specific Invoice Processing

Type de record:

paper
Créateur:
Avinash Malladhi
Éditeur:
Zenodo
Hôte:avatar

In the rapidly evolving digital world, businesses worldwide process a myriad of invoices daily, originating from multiple countries. This heterogeneous nature presents challenges in terms of diverse formats, languages, and key identifiers. This paper introduces an advanced AI-OCR system aimed at efficiently identifying the country of origin of invoices by extracting and scoring unique invoice parameters specific to the United States, United Kingdom, Germany, Brazil, and South Africa. Utilizing advanced image preprocessing and feature extraction techniques, the system enhances the accuracy of parameter identification. Neural networks and deep learning models are subsequently employed to classify and weigh the identified parameters, allowing the system to pinpoint the invoice's country of origin. Preliminary results indicate a high level of accuracy, demonstrating the system's robustness against variations within regions and in the face of incomplete or poor-quality data. The paper concludes with potential scalability solutions, suggesting how the system can integrate more countries and sync with other business technologies.

Visit

doi.org

Tasks

optical character recognitioncomputer vision

Tags

Invoice Processing ,AI-OCR System ,Country Identification Multilingual Invoices Parameter Weighting

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode