OCR explained: making scanned PDFs searchable
By the Converterzilla Team
We build privacy-first PDF and image tools that run entirely in your browser. Our team has shipped JavaScript file-processing apps used by thousands every day, and we write here about the libraries, trade-offs and patterns we use.
OCR — Optical Character Recognition — turns images of text into actual text. A scanned document looks like a PDF but is technically a stack of pictures. Without OCR, you can't search inside it, copy from it, or edit it. With OCR, all of that becomes possible while the document still looks identical.
How modern OCR works
Modern engines like Tesseract use neural networks trained on millions of font samples. They handle dozens of languages, multiple writing directions, and unusual fonts surprisingly well. Accuracy on clean printed text is 95%+ — better than most humans transcribing.
The invisible-text-layer trick
OCR doesn't replace the original scan — it adds an invisible text layer behind it. Visually, the document looks identical to the source. But search ("Cmd-F"), text selection, and copy-paste now all work because the text is genuinely there, just invisible.
What hurts accuracy
- Low-resolution scans — under 200 DPI, OCR struggles
- Skewed pages — most engines deskew automatically, but extreme angles break it
- Unusual fonts — script, decorative, hand-drawn fonts
- Handwriting — best-effort even with the best engines
- Multi-column layouts — OCR sometimes mixes columns into a single flow
Language support
Tesseract supports 100+ languages. For mixed-language documents (English + Spanish, say), pick both — the engine handles it. Wrong language selection drops accuracy noticeably.
Our OCR PDF tool will offer all major languages with auto-deskew and a hidden text layer. Coming with the next backend release.