PDF Table Extraction looks easy - until it fails in production.
PDF Table Extraction looks easy - until it fails in production.
Real-world bank statements are a nightmare for standard #Java parsers. You aren’t just dealing with text; you’re dealing with: scanned pages, shifting layouts, merged cells, and wrapped rows.
This #InfoQ article by Mehuli Mukherjee shows how stream parsing, lattice/OCR, validation, scoring, and selective ML improved extraction reliability for real banking systems.
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Redesigning Banking PDF Table Extraction: A Layered Approach with Java
PDF table extraction often looks easy until it fails in production. Real bank statements can be messy, with scanned pages, shifting layouts, merged cells, and wrapped rows that break standard Java parsers. This article shares how we redesigned the approach using stream parsing, lattice/OCR, validation, scoring, and selective ML to make extraction more reliable in real banking systems.
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