How to Extract Text from Images and Screenshots Using OCR (Free)

You have a screenshot of a long quote, a photo of a business card, a scanned document you need to edit, or an image with code examples you want to copy. Retyping that text manually is a waste of time. OCR — Optical Character Recognition — extracts the text automatically, and modern AI-powered OCR tools are astonishingly accurate.

What is OCR and how does it work?

OCR (Optical Character Recognition) is the technology that converts images of text into machine-readable, copyable text. The first OCR systems in the 1960s relied on templates that matched characters pixel-for-pixel against a database — they only worked with specific fonts at specific sizes.

Modern OCR uses deep learning. Convolutional neural networks analyse the visual patterns of characters across fonts, sizes, handwriting styles, lighting conditions, and languages. The model identifies probable character sequences and uses language models to resolve ambiguous cases — distinguishing a lowercase “l” from the number “1” based on context, for example.

The result is OCR that works reliably across printed text in hundreds of fonts, multiple languages, complex layouts with columns, tables and mixed content, and even reasonably legible handwriting.

Common OCR use cases

• Screenshots and screen captures — Copy code snippets, error messages, or text from app screenshots without retyping.
• Scanned documents — Extract text from scanned contracts, invoices, forms, and reports to make them searchable and editable.
• Business cards — Digitise contact information quickly from a photo.
• Book and magazine pages — Extract passages from scanned books or articles for quoting or note-taking.
• Receipts and invoices — Extract totals, line items, and vendor information for expense reports or bookkeeping.
• Whiteboard photos — Capture the text from a meeting whiteboard photo into a document without rewriting everything.
• Signage and labels — Translate or process text on signs, product labels, or packaging captured in photos.

Step-by-step: extracting text from an image

1. Open the Image to Text OCR tool and upload your image. Supported formats include JPG, PNG, WebP, and PDF page images.
2. Select the language of the text if the tool offers this option. Most tools default to English, but specifying the correct language improves accuracy significantly for non-Latin scripts.
3. Click Extract Text. The tool returns the recognised text in a copyable text box.
4. Review the extracted text for errors. OCR is typically 99%+ accurate on clean, high-contrast printed text, but accuracy drops for handwriting, stylised fonts, or poor image quality.
5. Copy the text and paste it where you need it. You can also pass it to the AI Text Summarizer if the extracted content is a long document you want to distil.

Tips for better OCR accuracy

OCR accuracy is heavily dependent on image quality. Follow these best practices:

• High contrast. Black text on white paper is ideal. Avoid coloured backgrounds with low contrast against the text colour.
• Sharp focus. Even a slight blur significantly reduces accuracy. For phone photos, tap the text to focus before shooting.
• Straight alignment. Skewed or perspective-distorted text is harder to read. Straighten the image or use a scanning app that auto-corrects perspective.
• Sufficient resolution. Text should be at least 10–12 pixels tall in the image. For a document with 12pt font, aim for at least 200 DPI — 300 DPI is better for higher accuracy.
• Clean background. Remove shadows, wrinkles, or overlapping text that obscures characters.

OCR accuracy by image type

Summary

OCR has become fast, accurate, and free. The ToolsGravity Image to Text OCR tool processes your images entirely in the browser, keeping your documents private while delivering results in seconds. For printed text and digital screenshots, accuracy is near-perfect. Improve results by shooting at high resolution, keeping the text in sharp focus, and ensuring good contrast between text and background.