Guide

How to Clean OCR Text from a Resume or Form

OCR (Optical Character Recognition) tools extract text from images and scans, but the output is rarely clean. You usually end up with broken lines, strange spacing, or garbled characters that need fixing before the text is usable. Here's how to deal with it.

What OCR output typically looks like

When you extract text from a scanned resume or form using an OCR tool, the raw output often has these problems:

Broken line wraps
Software En
gineer with 5
years experience
Double spaces
React  and  Node.js  developer
Space before punctuation
Experience : 5 years
Mixed empty lines
Name


John Smith


Email

Which preset to use

Resume / CV

Use this for most resume and CV text. It merges wrapped lines into paragraphs and preserves section breaks.

Form / Invoice

Use this for structured forms, invoices, and tables extracted as text. Behaves the same as Resume but the label is more descriptive.

List

Use this if each line is a separate item that should stay on its own line — for example, a list of skills or bullet points.

Generic

Use this for everything else — general paragraphs, letters, and documents that don't fit the above.

Step-by-step

1
Copy the OCR output
Run your image through an OCR tool (Google Docs, Adobe Acrobat, or any scanner app) and copy the extracted text.
2
Paste into Image Text Cleanup
Open the Image Text Cleanup tool and paste the raw text into the input box on the left.
3
Choose a preset
Select Resume, Form, List, or Generic depending on what kind of content you're cleaning.
4
Click Clean text
The backend processes the text and returns a cleaned version on the right.
5
Copy and use
Click Copy output. Paste the result wherever you need it — a document, email, or another tool.

What the tool cannot fix

  • Substituted characters — if OCR read 'l' as '1' or 'O' as '0', those need manual correction
  • Missing words — if the scanner missed a word entirely, no cleanup tool can recover it
  • Garbled text from very low-resolution or rotated scans
  • Non-Latin scripts — the cleanup logic is designed for Latin-alphabet text

Related tools