ExtractPDF4J/ExtractPDF4J

Java PDF table extraction & OCR library. Extract structured tables from text-based and scanned PDFs using stream, lattice (OpenCV-style grid detection), and hybrid parsing.

What it solves

ExtractPDF4J eliminates the need to manually retype data from PDF tables, specifically targeting documents that are difficult to parse, such as scanned invoices, bank statements, and financial reports. It provides a way to extract clean rows and columns even when a PDF lacks a text layer.

How it works

The library uses a multi-strategy approach to identify and extract tabular data:

  • StreamParser: Extracts data from text-based PDFs using text positions via PDFBox.
  • LatticeParser: Handles scanned or ruled PDFs by rendering pages to images and using OpenCV to detect lines and grids.
  • OcrStreamParser: Uses Tesseract OCR to extract text from image-heavy documents where no text layer exists.
  • HybridParser: Orchestrates these strategies to automatically select the best method for the document.

Who it’s for

It is designed for developers building production-grade document processing pipelines, specifically for fintech, banking platforms, analytics platforms, and AI/ML data preparation workflows.

Highlights

  • Native OCR Support: Handles scanned and image-based PDFs without requiring external text layers.
  • Java-Native: Built for Java 17+ and available via Maven Central.
  • Flexible Output: Supports exporting extracted tables to CSV or JSON formats.
  • Declarative Configuration: Offers annotation-based configuration for defining parser settings.
  • Deployment Ready: Includes a Spring Boot microservice wrapper and Docker support for easy API deployment.

Related

  • Project
    nguyenq/tess4j

    Tess4J is a Java JNA wrapper for the Tesseract OCR API that allows developers to extract text from various image formats and PDF documents.

  • Project
    scribeocr/scribe.js

    A JavaScript library for performing OCR and text extraction from images and PDFs, capable of creating searchable PDFs with invisible text layers.

  • Project
    firecrawl/pdf-inspector

    pdf‑inspector is a Rust‑based library (with Python, Node, and WASM bindings) that rapidly classifies PDFs, extracts position‑aware text, and converts it to clean Markdown. It can route only the pages that need OCR to a local model, saving time and cost. Benchmarks show it faster and more accurate than similar tools on a 200‑PDF test set.

  • Project
    opendataloader-project/opendataloader-pdf

    OpenDataLoader PDF is an open‑source PDF parser that converts PDFs (including scanned ones) into Markdown, JSON with element bounding boxes, HTML, and auto‑tagged PDFs. It offers a fast deterministic Java‑based local engine plus an optional hybrid AI mode for complex tables, OCR, formula extraction, and image description, achieving top benchmark scores. The free core (Apache‑2.0) handles layout analysis and auto‑tagging; enterprise add‑ons provide full PDF/UA compliance and a visual accessibility studio.

  • Project
    harshankur/officeParser

    officeParser is a TypeScript‑based Node.js and browser library that parses many office file formats (DOCX, PPTX, PDF, LaTeX, etc.) into a strict abstract syntax tree (AST) and can generate the same content back into formats like DOCX, HTML, PDF, Markdown, LaTeX, EPUB and RAG‑ready chunks. It includes a CLI, OCR support, password handling, template‑based mail‑merge, a native PDF engine, and an interactive web visualiser.