Image to Text Online Free
Extract text from images online free using OCR. Supports PNG, JPG, WebP, TIFF, and printed or typed text in 20+ languages. Runs entirely in your browser.
Click or drag an image here
PNG, JPG, WebP, BMP, TIFF, GIFHow to Extract Text from an Image
- 1Upload your image (PNG, JPG, WebP, TIFF, or BMP) by clicking the upload area or dragging it in.
- 2Select the language of the text in the image from the language dropdown. Always match the language to your document — wrong language selection is the most common cause of garbled output.
- 3Click Extract Text. Tesseract.js processes the image entirely in your browser — nothing is sent to any server.
- 4Copy the extracted text directly or download it as a
.txtfile for use in any document editor.
About OCR — Optical Character Recognition
OCR (Optical Character Recognition) is the technology that reads and extracts printed or typed text from images. This tool uses Tesseract.js — a WebAssembly port of the industry-standard Tesseract OCR engine originally developed at HP and now maintained by Google — to process images at near-native speed, all inside your browser tab without any server involvement.
OCR works best on clear, high-resolution images with strong contrast between the text and background. Scanned documents, screenshots, and photographed pages all work well when the image quality is adequate. For best results, use images at 300 DPI or higher with level, unrotated text. Supported languages include English, French, German, Spanish, Italian, Portuguese, Dutch, Russian, Chinese (Simplified and Traditional), Japanese, Korean, Arabic, Hindi, and more.
Image Quality Guide for OCR Accuracy
| Input Type | Expected Accuracy | How to Improve |
|---|---|---|
| Printed document scan at 300 DPI | Excellent (95–99%) | Ensure flat, well-lit scan |
| High-res screenshot of text | Excellent (95–99%) | Use full-size screenshot, no compression |
| Phone photo of document | Good (85–95%) | Use good lighting, hold camera level |
| Low-res image (under 150 DPI) | Moderate (60–80%) | Upscale image before uploading |
| Image with shadows or glare | Moderate (60–80%) | Convert to greyscale, increase contrast |
| Rotated or skewed text | Poor (30–60%) | Deskew image before uploading |
| Handwritten text | Poor (10–40%) | Use a dedicated handwriting OCR service |
| Decorative or stylised fonts | Variable | Results depend heavily on font clarity |
Tips to Improve OCR Accuracy
Select the Right Language First
Always match the language dropdown to the text in your image before clicking Extract Text. Using the wrong language model is the single most common cause of garbled output — especially for non-Latin scripts.
Use High-Resolution Images
OCR accuracy drops sharply at low resolution. Aim for 300 DPI minimum for scanned documents. For phone photos, get close enough that individual letters are clearly visible at 100% zoom.
Maximize Contrast
Dark text on a white background gives Tesseract the clearest signal. If your image has low contrast (grey text, coloured backgrounds, shadows), adjust brightness and contrast in any image editor before uploading.
Straighten the Image
Rotated or skewed text — even a few degrees off horizontal — significantly reduces accuracy. Deskew the image before uploading and crop out decorative borders or unrelated elements surrounding the text.
Pre-process with Greyscale
If an image has uneven lighting, shadows, or glare, convert it to greyscale or black-and-white before uploading. A clean high-contrast monochrome version often extracts far more accurately than the original colour photo.
Proofread High-Stakes Output
OCR is probabilistic and makes occasional errors on visually similar characters (0/O, 1/l/I). For legal, medical, or financial documents, always proofread the extracted text against the original image before use.
Frequently Asked Questions
What image formats does the OCR tool support?
The tool accepts PNG, JPG/JPEG, WebP, TIFF, and BMP. Support for HEIC (iPhone photos) and AVIF depends on your browser — they work in recent Chrome and Safari. If your image is in an unsupported format, convert it to PNG or JPG using the Image Converter tool first.
How do I get better OCR accuracy?
Accuracy depends on four factors: resolution (use 300 DPI or higher), contrast (dark text on a light background), orientation (text lines should be horizontal), and language selection (always match the dropdown to the text in your image). Of these, selecting the wrong language is the most common cause of garbled output.
Can I extract text from a scanned PDF?
Not directly — this tool processes image files. To OCR a scanned PDF, use a PDF tool to export the pages as images (PNG or JPG), then upload each image here. For digitally-created PDFs with an embedded text layer, the PDF to Word converter extracts text without needing OCR.
Does the image get uploaded to a server?
No. The OCR engine (Tesseract.js) runs as WebAssembly inside your browser. Your image files are never sent to any server — processing happens entirely on your device. This makes the tool safe to use with confidential documents, medical records, and private photos.
Why does OCR work on typed text but not handwriting?
Tesseract's standard models are trained on printed and typed characters. Cursive handwriting and calligraphy use connected strokes that differ fundamentally from the separated character shapes in the training data. For handwritten notes, dedicated handwriting-recognition services (Google Document AI, Microsoft Azure AI Vision) use separate models that handle connected strokes.
What languages does the OCR support?
The tool supports 20+ languages including English, French, German, Spanish, Italian, Portuguese, Dutch, Russian, Chinese (Simplified and Traditional), Japanese, Korean, Arabic, and Hindi. Select the correct language before processing — using the wrong language model is the single most common cause of poor results on non-English text.
Why are some characters misread (0 vs O, 1 vs l)?
OCR is probabilistic — it estimates each character from its visual shape. Visually similar characters (0 and O, 1 and l and I, rn and m) are the most common source of confusion. At lower resolutions, these characters' shapes become nearly identical at the pixel level. Higher resolution (300 DPI+) and good contrast reduce but do not eliminate these errors. Always proofread extracted text for high-stakes use.
Can I process multiple images at once?
The tool processes one image at a time. For multiple images, open the tool in separate browser tabs. For batch processing of hundreds of pages, a command-line workflow using the Tesseract desktop application or a cloud OCR API is more efficient.