Araştırma Makalesi

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

Cilt: 4 Sayı: 1 30 Ağustos 2024
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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

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

Kaynakça

  1. Open Source Data Labeling | Label Studio. (n.d.). Label Studio. https://labelstud.io/
  2. Ultralytics. (n.d.). GitHub - ultralytics/ultralytics: NEW - YOLOv8 in PyTorch > ONNX > OpenVINO > CoreML > TFLite. GitHub. https://github.com/ultralytics/ultralytics
  3. PaddlePaddle. (n.d.). GitHub - PaddlePaddle/PaddleOCR: Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices). GitHub. https://github.com/PaddlePaddle/PaddleOCR
  4. M. S. Satav, T. Varade, D. Kothavale, S. Thombare and P. Lokhande, "Data Extraction From Invoices Using Computer Vision," 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS), RUPNAGAR, India, 2020, pp. 316-320, doi: 10.1109/ICIIS51140.2020.9342722.
  5. D. A. Kosiba and R. Kasturi, "Automatic invoice interpretation: invoice structure analysis," Proceedings of 13th International Conference on Pattern Recognition, Vienna, Austria, 1996, pp. 721-725 vol.3, doi: 10.1109/ICPR.1996.547263.
  6. H. Sidhwa, S. Kulshrestha, S. Malhotra and S. Virmani, "Text Extraction from Bills and Invoices," 2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India, 2018, pp. 564-568, doi: 10.1109/ICACCCN.2018.8748309.
  7. Tesseract-Ocr. (n.d.). GitHub - tesseract-ocr/tesseract: Tesseract Open Source OCR Engine (main repository). GitHub. https://github.com/tesseract-ocr/tesseract
  8. R. Smith, "An Overview of the Tesseract OCR Engine," Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), Curitiba, Brazil, 2007, pp. 629-633, doi: 10.1109/ICDAR.2007.4376991.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Görüntü İşleme, Modelleme ve Simülasyon

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Ağustos 2024

Gönderilme Tarihi

6 Aralık 2023

Kabul Tarihi

30 Ağustos 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 4 Sayı: 1

Kaynak Göster

APA
Emel, M. H., Terzioğlu, M., & Özkan, R. (2024). Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions. Advances in Artificial Intelligence Research, 4(1), 10-17. https://doi.org/10.54569/aair.1401234
AMA
1.Emel MH, Terzioğlu M, Özkan R. Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions. Adv. Artif. Intell. Res. 2024;4(1):10-17. doi:10.54569/aair.1401234
Chicago
Emel, Mehmet Hilmi, Murat Terzioğlu, ve Ramazan Özkan. 2024. “Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions”. Advances in Artificial Intelligence Research 4 (1): 10-17. https://doi.org/10.54569/aair.1401234.
EndNote
Emel MH, Terzioğlu M, Özkan R (01 Ağustos 2024) Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions. Advances in Artificial Intelligence Research 4 1 10–17.
IEEE
[1]M. H. Emel, M. Terzioğlu, ve R. Özkan, “Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions”, Adv. Artif. Intell. Res., c. 4, sy 1, ss. 10–17, Ağu. 2024, doi: 10.54569/aair.1401234.
ISNAD
Emel, Mehmet Hilmi - Terzioğlu, Murat - Özkan, Ramazan. “Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions”. Advances in Artificial Intelligence Research 4/1 (01 Ağustos 2024): 10-17. https://doi.org/10.54569/aair.1401234.
JAMA
1.Emel MH, Terzioğlu M, Özkan R. Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions. Adv. Artif. Intell. Res. 2024;4:10–17.
MLA
Emel, Mehmet Hilmi, vd. “Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions”. Advances in Artificial Intelligence Research, c. 4, sy 1, Ağustos 2024, ss. 10-17, doi:10.54569/aair.1401234.
Vancouver
1.Mehmet Hilmi Emel, Murat Terzioğlu, Ramazan Özkan. Efficient and Accurate Date Extraction from Invoices: A Comprehensive Three-Step Methodology Integrating Custom Object Detection, OCR, and Refined Regular Expressions. Adv. Artif. Intell. Res. 01 Ağustos 2024;4(1):10-7. doi:10.54569/aair.1401234

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