Turn Scanned Documents into Searchable, Actionable Information

Organizations still handle large volumes of scanned documents, PDFs, and images that contain valuable information but cannot be indexed or searched. LogicalDOC’s Optical Character Recognition (OCR) engine transforms these “silent” documents into fully searchable assets, enabling fast retrieval, automated classification, and seamless integration into business workflows.

OCR is essential for digitizing archives, processing incoming mail, and extracting information from any raster-based document.

Full-Text OCR: Make Every Document Searchable

LogicalDOC automatically recognizes text within scanned images and raster PDFs, converting it into searchable content. Once processed, documents become fully indexable, allowing users to locate information instantly using LogicalDOC’s powerful search engine.

Key Capabilities

• Converts scanned documents and images into searchable text

• Supports multiple languages

• Integrates with the full-text indexing engine

• Runs automatically in the background

• Ideal for digitization projects and legacy archives

Zonal OCR: Extract Key Fields Automatically

Beyond full-text recognition, LogicalDOC also offers Zonal OCR, a powerful feature designed to extract specific data fields from structured or semi‑structured documents.

Zonal OCR allows you to define “zones” on a document template—such as invoice number, date, total amount, customer code, or reference ID—and automatically capture those values as metadata.

Perfect for

• Invoices and accounting documents

• Delivery notes and logistics forms

• Standardized business forms

• Repetitive documents with a consistent layout

Benefits

• Eliminates manual data entry

• Ensures consistent metadata extraction

• Accelerates workflow automation

• Reduces human error

OCR vs. Zonal OCR: What’s the Difference?

How OCR Works in LogicalDOC

Document Upload A scanned document or raster PDF is added to the repository. OCR Processing LogicalDOC identifies text using the configured OCR engine. Indexing Extracted text is indexed for fast retrieval. Search & Automation Users can search inside the document, and workflows can use extracted data. With Zonal OCR, an additional step occurs: Field Extraction Predefined zones extract metadata values and attach them to the document.

Supported OCR Engines

LogicalDOC supports multiple OCR engines to accommodate different performance, accuracy, and licensing requirements:

• Tesseract OCR (open-source, multilingual)

• Power PDF Advanced (optional commercial engine)

• OCRWebService – Cloud-based OCR engine suitable for high-accuracy recognition, multi-language support, and scenarios where local processing is not preferred

Administrators can configure engines, languages, timeouts, and processing rules directly from the OCR settings panel.

Performance and Best Practices

To ensure optimal performance:

• Limit OCR to relevant file types using include/exclude rules

• Configure batch size and timeout based on server capacity

• Use Zonal OCR for structured documents to reduce processing time

• Avoid OCR on documents that already contain embedded text

More details are available in the official documentation.

Use Cases

• Digitizing historical archives

• Processing incoming invoices

• Extracting key fields from logistics documents

• Making scanned contracts fully searchable

• Automating classification and routing workflows

Learn More

By combining full‑text OCR with advanced Zonal OCR capabilities, LogicalDOC enables organizations to transform scanned documents into structured, searchable, and actionable information. These technologies support faster retrieval, more reliable data extraction, and smoother automation across the entire document lifecycle.

For organizations looking to enhance the accuracy and efficiency of their document processes, LogicalDOC provides a robust and scalable foundation ready to support even the most demanding scenarios.

• OCR Settings Documentation https://docs.logicaldoc.com/en/settings/ocr

• Zonal OCR Documentation https://docs.logicaldoc.com/en/document-metadata/zonal-ocr