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

arXiv: https://arxiv.org/abs/2507.07029 · HTML: https://mlsanity.com/paper/2507.07029/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 5 references that are in the map.
- First posted on arXiv 9 Jul 2025.

## Built on by (most cited first, 1 of 1)

- [OCRTurk: A Comprehensive OCR Benchmark for Turkish](https://mlsanity.com/paper/2602.03693/) (2026)

## Abstract (arXiv)

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.