Convert a JPG, PNG, or WebP picture to editable text with OCR that runs in your browser. Choose the source language, review the recognized text, then copy it or download a plain-text file.
Image to Text (OCR)
Extract text locally with Tesseract.js OCR
📸
Click to upload or drag and drop
Supports JPG, PNG, WebP
Browser-based OCR: Tesseract.js performs recognition on your device. The selected language model may be downloaded by your browser, but your image and extracted text are not sent to Mizakii.
📄Documents
Extract text from scanned documents, receipts, invoices, and business cards instantly.
📸Screenshots
Convert text from screenshots, social media posts, and images to editable text.
🌍Multilingual
Select from 10 languages including English, Spanish, French, German, Chinese, and Japanese.
🔒Private
Recognition runs locally in this browser tab; Mizakii does not receive the selected image or output.
Documented product test
What We Tested on August 9, 2026
We ran the same English Tesseract.js engine used by this page against two generated PNG fixtures. Each contained an invoice number, a dollar amount, and a date on three lines. One used high-contrast black text; the other used smaller gray text on an off-white background.
Fixture
Result
Engine confidence
40 px black Arial on white
All 66 expected characters recognized
95
28 px gray Arial on off-white
All 66 expected characters recognized
95
This is a reproducible smoke test, not a general accuracy guarantee. Photos, handwriting, unusual fonts, skew, and complex layouts can perform much worse. For important records, compare every value with the source image. Read the OCR accuracy and troubleshooting guide before processing difficult images.
How to Convert Text in an Image to Text
1. Upload your image
Upload a photo, screenshot, or scanned document in JPG, PNG, or WebP format. You can also drag and drop directly onto the tool.
2. Extract the text
The selected Tesseract.js language model recognizes visible characters and returns editable text. Always proofread names, dates, totals, and other important values.
3. Copy and use
Copy the extracted text to your clipboard and paste it anywhere — a document, email, spreadsheet, or translation tool. No retyping needed.
Common Use Cases
Screenshots
Extract text from screenshots of articles, chats, or error messages you cannot copy directly.
Scanned Documents
Convert scanned PDFs, contracts, or printed documents into editable digital text.
Photos of Text
Photograph a whiteboard, sign, book page, or handwritten note and extract the text instantly.
Receipts & Invoices
Pull text from photos of receipts or invoices for expense tracking and record-keeping.
Foreign Language Text
Extract text from images in any language so you can paste it into a translation tool.
Inaccessible Content
Convert text locked inside image files into accessible, searchable, and editable content.
Supported Image Formats
JPG / JPEGPNGWebP
Supported Languages
Choose one of the 10 available recognition languages before extraction. Selecting the correct source language improves recognition; this tool does not auto-detect it.
What is OCR — and How Does Image to Text Conversion Work?
OCR stands for Optical Character Recognition. It is a technology that reads and interprets text inside an image file the same way a human would read a printed page — by analysing the visual shapes of letters and words. The difference is that OCR does it in milliseconds and outputs machine-readable text you can edit, search, and copy.
This page uses Tesseract.js, a WebAssembly and JavaScript port of the open-source Tesseract OCR engine. It identifies text regions and characters using the language you select, then returns plain text. Recognition is not document reconstruction: columns, tables, spacing, and reading order may not match the source.
Before online OCR tools existed, extracting text from a scanned document or screenshot meant retyping it manually — a slow process prone to errors. Today, any image containing readable text can be converted to editable text in seconds, directly in your browser, without installing software or creating an account.
Expected Accuracy by Image Type
Image type
Accuracy
Notes
Screenshot (digital text)
★★★★★ Excellent
Highest accuracy — text is sharp and high-contrast by nature
Printed document (scanned at 300 DPI+)
★★★★★ Excellent
Near-perfect for standard fonts and clean layouts
Photo of printed text (good lighting)
★★★★☆ Very Good
Minor errors possible with unusual fonts or low contrast
Photo of handwritten text (block letters)
★★★☆☆ Good
Works well for clear block handwriting; inconsistent results for casual writing
Low-resolution or blurry image
★★☆☆☆ Fair
Improve by cropping tightly and increasing brightness before uploading
Cursive or stylised handwriting
★☆☆☆☆ Poor
Not reliable — manual transcription recommended
Image to Text vs Manual Transcription
Method
Speed
Accuracy
Best for
OCR (this tool)
Seconds
High (clear images)
Printed text, screenshots, scanned docs
Manual typing
Slow
Human error risk
Short snippets only
Copy-paste
Instant
Perfect
Digital text only — not images
Desktop OCR software
Medium (setup)
High
Batch processing, local privacy
Tips for Accurate Text Extraction
OCR accuracy depends almost entirely on image quality. These are the most common reasons an extraction comes back garbled — and how to fix them before you upload.
Use a high-resolution image
Low-resolution images make characters look like blobs of pixels. For scanned documents, scan at 300 DPI or higher. For photos, get as close to the text as possible before shooting.
Ensure good contrast
Black text on a white background extracts near-perfectly. Low-contrast combinations — grey text on light grey, dark text on a dark background photo — cause the most errors.
Keep the image straight
Severely skewed or rotated images reduce accuracy. Most phone camera apps have a document scan mode that automatically corrects perspective — use it.
Avoid blurry or noisy images
Motion blur and compression artefacts (common in JPEG screenshots saved at low quality) confuse the character recognition. Use PNG for screenshots.
Printed text outperforms handwriting
Printed and typed fonts extract reliably. Casual handwriting is harder, especially with overlapping letters or inconsistent sizing. Block handwriting works better than cursive.
Crop before uploading
If you only need text from one area of a large image, crop it first. A tighter image means faster processing and less chance of the engine picking up background noise.
What to Do After Extracting Text
Once you have the extracted text on your clipboard, here are the most common next steps:
Translate it
Paste the text into Google Translate, DeepL, or any translation tool. This is the fastest way to read signage, foreign-language documents, or product labels photographed abroad.
Import into a spreadsheet
If the image contained a table, numbers, or a list, paste the extracted text into Excel or Google Sheets. Clean up the spacing and you have editable data without manual entry.
Search and reference
Extracted text is fully searchable. Paste a long document into Google Docs and use Ctrl+F to find specific clauses, names, or figures — something impossible with an image file.
Feed into an AI tool
Paste extracted text into ChatGPT, Claude, or Gemini to summarise it, answer questions about it, or reformat it. OCR turns image-locked content into AI-usable input.
Edit and reformat
Use a markdown editor or word processor to clean up the extracted text, fix formatting, and repurpose it for your own document, blog post, or report.
Archive as searchable text
Save the extracted text alongside the original image in your notes app or document system. It makes scanned receipts, contracts, and forms searchable years later.