Image to Text
Free OCR tool to extract text from images online — the fastest, safest way to convert photos, screenshots, scanned documents, handwritten notes, PDFs, and pictures of text into editable, searchable, copy-pasteable text. Powered by Tesseract.js running entirely in your browser with no server uploads. Supports 12 languages (English, Spanish, French, German, Italian, Portuguese, Chinese Simplified, Japanese, Korean, Arabic, Hindi, Russian) with image preprocessing (grayscale, contrast enhancement) for higher accuracy on tough images. Perfect for students digitising textbook pages, professionals extracting text from business cards and receipts, developers grabbing text from screenshots, researchers digitising printed documents, and anyone who needs text from an image they cannot type out manually. No signup, no watermark, no daily limit, no upload to any server — 100% browser-based, even your phone camera captures stay on your device.
Drop image here or click to upload
JPG, PNG, WebP, BMP, GIF — Max 20 MB
100% Private
Your images are processed entirely in your browser. Nothing is uploaded to any server.
12 Languages
Extract text in English, Spanish, French, German, Chinese, Japanese, Korean, Arabic and more.
All Formats
Supports JPG, PNG, WebP, BMP and GIF images. Upload files, paste from clipboard or use camera.
How to Extract Text from Images Online
- Upload your image — Drag and drop, click to browse, paste from clipboard (Ctrl+V) or capture with your camera on mobile devices.
- Select the language — Choose the language of the text in your image. English is selected by default. For best results, match the language to the text in the image.
- Click Extract Text — The OCR engine processes your image entirely in your browser. You will see a progress bar as the text is recognized.
- Copy or download — Once extracted, copy the text to your clipboard, download it as a .txt file, or edit it directly in the output box.
Supported Image Formats
This OCR tool accepts all common image formats:
- JPEG/JPG — Photographs, scanned documents, screenshots
- PNG — Screenshots, diagrams, text on transparent backgrounds
- WebP — Modern web images from Chrome screenshots
- BMP — Bitmap images from older scanners
- GIF — Static GIF images with text content
Tips for Better OCR Accuracy
- Use clear images — Higher resolution images produce more accurate results. Avoid blurry or low-quality photos.
- Good lighting — When photographing documents, ensure even lighting without shadows or glare.
- Straight alignment — Text that is straight and horizontal is recognized more accurately than tilted text.
- Enable preprocessing — Turn on Grayscale and Enhance Contrast for scanned documents or photos with uneven lighting.
- Select the correct language — Choosing the right language for your text significantly improves accuracy.
Who Uses Image to Text Conversion
- Students extract text from textbook photos, lecture slides and handwritten notes to create searchable digital notes.
- Writers and editors digitize printed content, quotes from books and research materials for articles and publications.
- Business professionals convert receipts, invoices, business cards and printed documents into editable text.
- Developers extract error messages, code snippets and log output from screenshots for debugging and documentation.
- Researchers digitize historical documents, survey responses and printed data tables for analysis.
Why Use an Online Image-to-Text Converter?
Typing out text from an image or a screenshot is one of the most universally annoying tasks in modern life. A photo of your textbook page, a receipt you need for an expense report, a screenshot of an error message you want to Google, a snapshot of a whiteboard at the end of a meeting, a foreign-language menu — all of these contain text you want as digital, editable, copy-pasteable text. Online OCR (Optical Character Recognition) tools turn that image-text into real text in seconds, replacing what would otherwise be 10–30 minutes of frustrating manual typing.
OCR powers an enormous range of workflows: searchable PDF archives, accessibility for screen readers, automated invoice processing, language translation pipelines, academic research digitisation, content moderation systems, legal document discovery, and even cheating-detection systems for online exams. The same technology that lets Google Photos find every receipt with "Starbucks" on it is what runs in this browser tab when you upload a photo.
This OCR tool focuses on three things competitors get wrong: privacy (your image never leaves your device, unlike Google OCR or Adobe Scan which both upload), simplicity (paste an image, click extract, get text — no signup, no API key, no "free tier with daily limits"), and multi-language support (12 languages including Hindi, Arabic, Chinese, Japanese — many free OCR tools are English-only).
OCR Languages Supported (12 Languages, Including Hindi, Arabic, Chinese, Japanese)
This OCR engine supports 12 of the world\'s most-used languages. Pick the language that matches your image content — selecting the right language dramatically improves accuracy. Here\'s the complete reference:
| Language | Native Script | Best For | Typical Accuracy |
|---|---|---|---|
| English | Latin (ABC) | Books, screenshots, receipts, business documents | 95–99% |
| Spanish | Latin with accents | Documents from Spain, Mexico, Latin America | 92–97% |
| French | Latin with accents | Documents from France, Canada (Quebec), Belgium | 92–97% |
| German | Latin with umlauts | German, Swiss, Austrian documents | 92–97% |
| Italian | Latin with accents | Italian documents and signage | 92–97% |
| Portuguese | Latin with accents | Brazilian and European Portuguese documents | 92–97% |
| Chinese (Simplified) | Han characters | Mainland China documents, modern Chinese text | 85–92% |
| Japanese | Hiragana, Katakana, Kanji | Japanese documents, manga text, signage | 85–92% |
| Korean | Hangul | Korean documents and text | 85–92% |
| Arabic | Arabic script (RTL) | Arabic documents from MENA region | 80–90% |
| Hindi (हिन्दी) | Devanagari | Hindi documents, textbooks, signage | 80–90% |
| Russian | Cyrillic | Russian documents and signage | 85–92% |
Tip: if your image contains text in multiple languages (e.g., English headings + Hindi body text), pick the dominant language. For mixed scripts, the tool may need multiple passes — one per language.
Is the Image to Text OCR Safe and Legal to Use?
100% Legal
Yes — using an OCR tool is completely legal everywhere. OCR (Optical Character Recognition) is a foundational technology used by Google Docs, Adobe Acrobat, Microsoft Office Lens, Apple\'s Live Text, and dozens of other major products. Reading printed text from a photograph is no different than typing it out manually — just faster. No license is required for personal, educational, or commercial use.
Important: the legality depends on the image content, not the OCR. If you legitimately have rights to the image (your own photos, your own scanned notes, public domain content), the extracted text is also yours. If the source is copyrighted, the text remains copyrighted — OCR doesn\'t create new rights. Don\'t OCR an entire copyrighted book and publish the text without permission.
100% Safe & Private
Yes — this OCR is safe even for sensitive content. All processing runs locally in your browser using Tesseract.js compiled to WebAssembly. There\'s nothing to install. Your images never touch a server. Verify it yourself: open browser DevTools Network tab, run an OCR — zero outbound requests carry your image.
No image uploads to our servers — pure client-side OCR No signups, no email collection, no tracking pixels Open-source Tesseract.js engine (audit the code yourself) No daily OCR limit, no file count cap Works fully offline after first language download Served over HTTPS with strict security headers
Who Uses an Image to Text Converter (Detailed Use Cases)
Online OCR powers an enormous range of workflows. Here are the most common ones:
Students & Researchers
Photograph textbook pages, lecture slides, handwritten notes, library books, and journal articles — convert them to searchable, editable text instantly. Build digital flashcards from physical books. Quote textbooks in essays without manual retyping.
Accountants & Bookkeepers
Extract data from receipts, invoices, and bank statements. Photograph stack of receipts at end of week, OCR them, paste into expense report. Massive time saver vs manual data entry.
Business Professionals
Digitise business cards into your CRM. Convert whiteboard photos after meetings into searchable notes. Extract text from charts and infographics for reports.
Developers & QA Engineers
Extract text from error message screenshots to Google. Pull code from screenshot-based bug reports. Convert command-line output screenshots into copy-pasteable text.
Travellers & Language Learners
Photograph foreign-language menus, signs, train schedules, product labels — extract text in source language, then translate. Use the multi-language OCR for Chinese, Japanese, Arabic, Hindi documents you can\'t read.
Accessibility Users
Convert images into text that screen readers can read. Make inaccessible PDF scans accessible. Help low-vision users access printed content via text-to-speech.
Why This Is the Best Free Image to Text OCR
Search for "image to text" and you\'ll find dozens of OCR options — Adobe Scan, Google Drive OCR, OnlineOCR.net, Convertio, Easy OCR. Most upload your image to a server (privacy concern), require signup, charge for non-English languages, or impose daily limits. Here\'s how we compare:
What We Do
- 100% browser-based — image NEVER leaves your device
- Free for everyone, all 12 languages included
- No signup, no email, no API key required
- No daily limit on OCR operations
- Open-source Tesseract.js engine (auditable)
- Image preprocessing (grayscale, contrast) for higher accuracy
- Drag-drop, paste, camera capture support
- Works offline after first language download
- Mobile-first design — works on phones & tablets
- Confidence score shown for output quality
What Other Sites Do
- Upload your image to a server (privacy risk)
- Require signup or email after 1-3 OCRs
- Charge for non-English languages
- Cap free tier at 5-20 images per day
- Use proprietary closed engines you can\'t audit
- No preprocessing options
- Upload-only interface (no paste or camera capture)
- Need internet for every OCR (no offline mode)
- Desktop-only UI broken on phones
- Show no quality indicator on output
How to Extract Text from an Image on Any Device
This OCR works identically across every device. Here are platform-specific workflows for the most common scenarios:
- Open this page in your phone\'s browser.
- Tap the upload zone — choose "Take Photo" to capture directly with the camera, or pick an existing photo from your gallery.
- Select the language of the text in the image.
- Tap Extract Text — wait for OCR to finish (10–30 seconds on first use, ~5 seconds after that).
- Tap Copy to grab the text, or Download to save as a .txt file.
- Take a screenshot (Windows: Win+Shift+S; Mac: Cmd+Shift+4; Linux: Print Screen).
- Open this page and press Ctrl+V — the screenshot pastes directly into the tool.
- Or drag-and-drop the saved screenshot file into the upload area.
- Pick the language and click Extract Text.
- Copy the extracted text to your clipboard or download as .txt.
- Photograph the page directly above the paper (avoid angles which distort text).
- Use natural daylight or even artificial lighting — avoid shadows.
- Upload to this tool and enable "Enhance Contrast" preprocessing for handwritten content.
- Pick the matching language (English, Hindi, etc.).
- Extract. For multi-page notes, repeat for each page — combine results in your notes app.
- Photograph in good light, flat on a surface, with the entire card/receipt in frame.
- Crop the photo (optional) to remove unrelated background.
- Upload, select English (or your language), enable preprocessing.
- Extract — the result is structured text you can paste into Excel, Sheets, or your CRM.
OCR Best Practices for Maximum Accuracy
Getting clean, accurate text out of OCR isn\'t magic — it depends a lot on the input image quality. Follow these patterns for the best results:
- Use the highest resolution photo possible. A blurry 800×600 photo of text yields 70–80% accuracy. A sharp 2000×1500 photo of the same text yields 95%+. Phone camera photos at default quality are usually fine.
- Match the language to the image content. Selecting "English" for a Hindi document will yield gibberish. The tool needs to know which character set to recognize.
- Use even, bright lighting. Shadows across text dramatically reduce accuracy. Daylight or even artificial light from multiple sides works best.
- Photograph at a 90-degree angle (straight overhead). Angled photos cause perspective distortion that confuses OCR. Hold the camera parallel to the paper.
- Enable preprocessing for low-contrast text. The "Grayscale" and "Enhance Contrast" options dramatically improve accuracy on faded scans, light-text-on-light-background, or shadowed documents.
- For handwritten text, write neatly in printed letters (not cursive). Modern OCR is good but cursive handwriting is still hard. Use larger letters and clear spacing.
- Avoid stylised or decorative fonts. Times, Arial, Helvetica, Courier all OCR well. Comic Sans, calligraphy fonts, and graffiti styles struggle.
- Crop the image to just the text area. Removing background (logos, photos, decoration) speeds up processing and improves focus on the actual text.
- Verify and clean up the output. Even 99% accuracy means 1 error per 100 characters. Always proofread OCR output before using it for anything important — especially for legal, medical, or financial content.
Frequently Asked Questions
Yes. This tool uses Tesseract.js, an OCR engine that runs entirely in your web browser using WebAssembly technology. Your images are never uploaded to any server. All processing happens locally on your device. You can verify this by checking the network tab in your browser developer tools — no image data is transmitted.
This tool supports 12 languages: English, Spanish, French, German, Italian, Portuguese, Chinese (Simplified), Japanese, Korean, Arabic, Hindi and Russian. Select the language from the dropdown before processing your image for the best accuracy.
On the first use, the tool downloads the language training data (typically 2-15 MB depending on the language). This data is cached by your browser, so subsequent extractions using the same language are significantly faster. The progress bar shows the download and recognition status.
The OCR engine works best with printed text and typed content. It can recognize some clear handwriting, but accuracy varies depending on how legible the handwriting is. For best results with handwriting, use high-resolution photos with good lighting and enable the Enhance Contrast option.
The maximum file size is 20 MB. Since processing happens in your browser, very large images may take longer to process depending on your device performance. For fastest results, use images under 5 MB.
Upload an image (drag-drop, paste from clipboard with Ctrl+V, or use your phone camera), select the language of the text in the image, and click Extract Text. The OCR engine runs in your browser and produces editable text in 5–30 seconds depending on image size. Copy the result to your clipboard or download as a .txt file. No signup, no upload to any server.
Take a screenshot (Windows: Win+Shift+S; Mac: Cmd+Shift+4; Linux: Print Screen), then either drag-drop the saved file into the OCR tool, or paste directly with Ctrl+V (the tool reads your clipboard). Pick English as the language and click Extract Text. Perfect for grabbing text from error messages, social media posts, online articles you can\'t copy-paste from, or anything else you can see on screen but can\'t select.
Yes — select Hindi (हिन्दी) from the language dropdown before clicking Extract Text. The Devanagari script is fully supported. Accuracy on printed Hindi text is typically 80–90%; handwritten Hindi is harder but still recognized for clearly-written notes. Same workflow applies to Arabic, Chinese, Japanese, Korean, Russian — just match the language selector to the image content.
The biggest difference: privacy. Google OCR, Adobe Scan, OnlineOCR.net all upload your image to their servers for processing. This tool runs OCR entirely in your browser using Tesseract.js — verify it yourself by opening DevTools Network tab during an OCR. Other differences: (1) No signup or email required. (2) No daily limit. (3) All 12 languages free (competitors charge for non-English). (4) Works offline after first language download. (5) Open-source engine you can audit. Adobe Scan is mobile-only; this works on any device.
Yes — the OCR works perfectly in mobile browsers (Chrome, Safari, Samsung Internet, Firefox). Open this page on your phone, tap the upload zone, choose "Take Photo" to use your camera directly OR pick an existing photo from your gallery, select language, and tap Extract Text. Everything runs in your phone\'s browser — no app installation needed. The extracted text can be copied to other apps or downloaded as a .txt file.
This tool processes images, not PDFs directly. To OCR a PDF: (1) Open the PDF and screenshot each page (or export pages as images using a PDF tool). (2) Upload each image to this OCR tool. (3) Combine the extracted text. For PDFs that already contain selectable text (not scanned images), you can copy-paste directly from the PDF — no OCR needed. OCR is only required for scanned PDFs that are essentially images of text.
OCR accuracy depends on input quality. Common causes of poor accuracy: (1) Image is blurry or low resolution — use a sharper photo. (2) Text is at an angle — reshoot directly overhead. (3) Wrong language selected — match the language dropdown to the image content. (4) Poor contrast (e.g., light grey text on white background) — enable the "Enhance Contrast" option. (5) Decorative or handwritten font — OCR works best on standard typefaces like Arial, Times, Helvetica. (6) Small text — very small text (under 8pt equivalent) doesn\'t OCR well.
Yes — OCR itself is a foundational technology used by Google, Adobe, Microsoft, and dozens of major products. Converting images of text into editable text is completely legal for personal, educational, and commercial use. The legal nuance is about the source content: you should have rights to the image you\'re processing. Your own photos, your own scanned notes, public domain content, properly licensed material: all fine. Copyrighted content owned by someone else: copyright still applies to the extracted text. Don\'t OCR and republish copyrighted books without permission.
Never. The output is clean plain text, exactly as extracted from your image — no watermarks, no "Powered by X" branding, no daily limit messages. Many competing tools add "OCR powered by [vendor]" footers to their free-tier outputs. We never do that.
Currently, the tool processes one image at a time for clarity and accuracy — you upload, extract, copy, repeat. For batch processing of large image sets (50+ photos), consider running each through individually and saving results to a notes app or text file. We may add bulk OCR support in a future update; for now, sequential processing is the workflow.