OCR Text Recognition: Why Searchable PDFs Make Your Business More Efficient

A scanned document is initially nothing more than an image. The computer sees pixels, not letters. Without OCR text recognition, a scan is not searchable, not copyable and not indexable. Optical Character Recognition (OCR) transforms this image into machine-readable text — turning a static scan into a living, usable document.

For organisations looking to digitise their paper archives, automate invoice processing or archive documents in a legally compliant manner, OCR is not optional technology — it is the fundamental prerequisite for every digital document process.

How Does OCR Work?

From pixel to letter in three steps

1. Image Pre-Processing

Before character recognition begins, the software optimises the scan image. This includes: straightening skewed pages (deskewing), removing spots and artefacts, adjusting contrast and brightness, and converting to black and white for better character separation. This pre-processing is crucial for subsequent recognition accuracy.

2. Character Recognition

The OCR engine analyses the optimised image and identifies individual characters by their shape. Modern engines use machine learning and neural networks trained on millions of font samples. They recognise not just individual letters but also consider context: word probabilities, language models and formatting patterns significantly improve accuracy.

3. Text Layer Creation

In the final step, the recognised text is placed as an invisible layer over the original image — the so-called sandwich PDF. The document looks like the original but contains a fully searchable text layer. Alternatively, the text can be exported as a standalone text document.

Sandwich PDF vs. Plain Text PDF

Two output formats with different use cases

Criterion	Sandwich PDF	Plain Text PDF
Content	Original image + invisible text layer	Extracted text only (no image)
Appearance	Identical to the original	Plain text, formatting partly lost
Searchability	Full-text search possible	Full-text search possible
File size	Larger (image + text)	Smaller (text only)
Use case	Archiving, compliance, legal certainty	Data extraction, further processing
Standard	PDF/A (long-term archiving)	No specific standard

For most business applications, the sandwich PDF is the right choice: it combines the fidelity of the original scan with the searchability and indexability of digital text. The PDF/A format additionally ensures that the document can still be opened and read decades from now.

Use Cases for OCR in Business

Where searchable PDFs deliver the greatest benefit

Full-Text Search in Digital Archives

Imagine searching for a specific invoice from 2023. Without OCR, you must open hundreds of scan files individually and browse through them manually. With OCR, you enter the invoice number in the search bar and find the document in seconds. Across thousands of documents, this saves hours per week.

Automatic Data Extraction

OCR is the foundation for automatic extraction of structured data from documents: invoice numbers, dates, amounts, IBAN numbers, supplier names. This data can be transferred directly to ERP systems, accounting software or DMS solutions — without manual typing.

Compliance and Audit Readiness

Many compliance requirements presuppose searchable documents. During tax audits, GDPR data subject requests or internal audits, documents must be found and provided quickly. OCR-processed documents in PDF/A format meet these requirements and are admissible as legal evidence.

Accessibility

Searchable PDFs are an important building block for digital accessibility. Screen readers can read aloud the text layer, allowing visually impaired persons to access the content of scanned documents. Without OCR, a scan is invisible to screen readers.

Tips for Better OCR Results

How to achieve the highest recognition accuracy

Choose the Right Resolution

300 DPI is the gold standard for OCR. At this resolution, modern engines achieve above 99% accuracy. 200 DPI may suffice for clear prints but leads to errors with small fonts. 400 DPI and above offers no advantage for standard documents but slows down scanning and produces larger files.

Optimise Contrast

High contrast between text and background improves recognition. Automatic image optimisation — as offered by Docuflair Flow — adjusts brightness, contrast and gamma individually for each page. Coloured backgrounds, watermarks or show-through effects can impair OCR quality.

Ensure Scan Quality

Clean originals, a well-maintained scanner and straight page feed are the foundation. Creases, spots, punch holes and staples can interfere with recognition. The automatic image cleanup in Docuflair Flow removes many of these interference factors before OCR analysis.

Set the Correct Language

OCR engines use language-specific dictionaries and models. Set the correct document language so the engine correctly recognises special characters and typical word structures. For multilingual documents, modern engines support automatic language detection.

Experience OCR Text Recognition in Action

Docuflair Flow integrates state-of-the-art OCR technology directly into your scan workflow. From scan to searchable PDF/A — fully automated and on-premises. Schedule a free demo.

Request Free Demo Discover Docuflair Flow

Frequently Asked Questions

Answers to the most important questions about OCR text recognition

What is the difference between a sandwich PDF and a plain text PDF?

A sandwich PDF contains the original scan image as the visible layer with an invisible text layer underneath. The document looks like the original but is searchable. A plain text PDF contains only the extracted text without the original image. For archiving, the sandwich PDF is the standard as it combines appearance and functionality.

What resolution delivers the best OCR results?

300 DPI is the gold standard for OCR text recognition. At this resolution, modern OCR engines achieve accuracy above 99 percent with clearly legible originals. 200 DPI may suffice for clear prints, while 400 DPI or higher is only needed for very small fonts or highly detailed originals.

Can OCR recognise handwritten text?

Modern OCR technologies can recognise neatly written block letters fairly well. With joined-up handwriting (cursive), the recognition rate drops significantly. For business-critical handwriting recognition (ICR), there are specialised solutions that require separate software and training.