Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices

Parshva Dhilankumar Patel
7/9/2025
cs.CVcs.AI

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Abstract

This paper presents the design and development of an OCR-powered pipeline for efficient table extraction from invoices. The system leverages Tesseract OCR for text recognition and custom post-processing logic to detect, align, and extract structured tabular data from scanned invoice documents. Our approach includes dynamic preprocessing, table boundary detection, and row-column mapping, optimized for noisy and non-standard invoice formats. The resulting pipeline significantly improves data extraction accuracy and consistency, supporting real-world use cases such as automated financial workflows and digital archiving.

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Cite this paper

@article{patel2025design,
  title  = {Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices},
  author = {Parshva Dhilankumar Patel},
  year   = {2025},
  eprint = {2507.07029},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.07029v1}
}

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