Run the scan through OCR, because there is no text in a scanned PDF to extract. OCR reads the picture and produces its best guess at the words, which is very good on a clean 300 DPI scan and unreliable on a phone photo.
Expect to lose layout. Columns, tables and headers are structure, and text-only output keeps words rather than structure.
The word extract sets the wrong expectation. Extracting text from a born-digital PDF is extraction: the characters are in the file and a tool reads them out. A scan contains no characters at all, only an image that happens to depict them.
Extraction versus recognition
This distinction explains why results vary so wildly between two documents that look equally readable on screen. The stages themselves, and what decides accuracy at each one, are covered in how OCR works on a PDF.
The text is stored in the file
- Characters stored as codes with a font reference
- Extraction is exact, with no guessing involved
- Reading order usually preserved
- No proofreading needed
The text has to be guessed
- Pages are photographs of printed characters
- OCR classifies each shape and may be wrong
- Accuracy depends on the scan, not the software
- Layout analysis can misread column order
What you lose
OCR produces words. Everything that made those words a document is a separate layer of information that plain text output cannot carry.
- The words themselvesKept
- Paragraph breaksUsually kept
- Bold and italicLost
- Table structureLost
- Multi-column orderOften scrambled
- Images and figuresLost entirely
Tables are the painful case. The engine may read every cell correctly and still hand you a stream of words with no indication of which column each belonged to. A financial table becomes a list of numbers in an order that is difficult to reconstruct, and for anything with more than a few rows it is often faster to retype it than to repair the output.
The mistakes OCR makes
Recognition errors are not random. They cluster around characters whose printed shapes are similar, which means you can search for them directly.
rnread asmand the reversel,1andIinterchangeable in many fonts0andOnear identical in some facesclread asdwhen letters touch5andSespecially at low resolution8andBin faded or thick print
Proofreading efficiently
Reading the whole output against the original is slow and mostly wasted effort, since most of it will be correct. Targeted checks find more errors in less time. If you run the scan through PDFslime's OCR PDF tool, its workspace boxes every word and colours the ones it was unsure of in red, which is the place to start.
Check every number against the page
Totals, dates, reference numbers, quantities. This is where errors are both most likely to survive and most damaging, because nothing corrects them automatically.
Search for the confusion pairs
Look for stray 1 inside words and l inside numbers. A handful of searches covers the most common substitutions across the whole document.
Read proper nouns carefully
Names, places and companies are not in the dictionary, so the language model cannot help and may do harm by correcting them towards real words.
Getting a better result
Almost all accuracy is decided before the software runs, which means the highest-value fix is usually to go back to the paper.
Rescanning at 300 DPI, in greyscale, straight on the glass, with the scanner's deskew enabled, will beat any amount of reprocessing of a poor image. If the original is not available, cleaning up contrast and straightening the existing image before recognition still helps, though it cannot recreate detail that was never captured.
Run recognition in your browser
The scan is read on your own machine, so neither the file nor the words in it are sent anywhere.
Common questions
Working with what comes back.
01Why can I not just copy the text out of my scan?
Because there is no text in it. The pages are photographs, so there is nothing for a copy operation to find. OCR has to read the image and produce text before anything can be copied.
02How accurate is OCR?
It depends on the scan far more than on the software, so judge each document rather than trusting a general figure. OCR PDF reports the average confidence for the file and marks the words it was least sure of, which tells you how much checking a given scan needs.
03Why did my table come out as a jumble?
Because OCR recognises characters, not structure. It can read every cell correctly and still have no way to record which column each belonged to. For anything but the simplest tables, retyping is often faster than repairing the output.
04Why is my two-column page interleaved?
Layout analysis misjudged the columns and read straight across the page instead of down each one. The words are correct and the order is not. Check the first few lines of output before relying on the rest.
05Which errors should I look for first?
Numbers, because no dictionary corrects them, and proper nouns, because the language model cannot help and sometimes makes them worse. Then search for the classic confusion pairs such as rn against m, and l against 1.
06Can I improve the result without rescanning?
Somewhat. OCR PDF turns sideways pages upright and straightens a crooked scan before reading, both on by default, and raising the contrast of faint print helps too. Detail that was never captured cannot be recovered, though, so if the paper is still available a rescan will do more than any of these.