Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915379803062272 |
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| author | Patel, Parshva Dhilankumar |
| author_facet | Patel, Parshva Dhilankumar |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07029 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices Patel, Parshva Dhilankumar Computer Vision and Pattern Recognition Artificial Intelligence I.2.10; I.4.9; H.3.1 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. |
| title | Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence I.2.10; I.4.9; H.3.1 |
| url | https://arxiv.org/abs/2507.07029 |