Searchable text layer
OCR is useful only when you know what you are asking it to recognize
This tool renders selected PDF pages, sends those page images to Tesseract running in the browser, and places recognized words back into the PDF as a nearly invisible searchable text layer. The original page image stays visible.
First test whether OCR is needed
Try selection
Drag across one sentence. If individual words do not highlight, the page may be image-only.
Try search
Search for a distinctive name or phrase you can clearly see. Zero results can indicate there is no useful text layer.
Try copy
Paste one short paragraph into a plain text editor. Empty or badly broken text is a clue that recognition is needed or unreliable.
The current OCR languages are specific
The workspace supports English, French and Spanish recognition. Choose the language that best matches the page. Mixed-language documents can still work unevenly and need extra review.
What affects recognition most
| Page condition | Likely effect |
|---|---|
| Correct orientation and sharp text | Better character recognition |
| Skewed or rotated pages | More missed or confused words |
| Heavy JPEG artifacts | Punctuation and narrow letters can degrade |
| Tables and multiple columns | Reading order can become unreliable |
| Handwriting | Accuracy can vary widely |
Review the fields where one wrong character matters
Names, dates, totals, account numbers, IDs and reference codes deserve direct comparison with the page image. OCR can mistake O for 0, I for 1, or lose punctuation while the visible scan still looks correct.
OCR makes text searchable; it does not make a PDF automatically accessible.
Accessibility also needs headings, reading order, table structure, language metadata, form labels and other semantic work.
A practical test after OCR
- Search for one known name.
- Search for one date or number.
- Copy a short paragraph and compare it with the image.
- Sample a difficult page with faint text, a table or unusual layout.
- Keep the original scan as the visual reference.
How local processing works here
The PDF page is rendered in your browser, and Tesseract performs recognition there. The OCR engine may download its JavaScript components and language data from a CDN, but the selected PDF itself is not uploaded to PDFNexa. The recognized words are written into a new PDF in the browser.