Drag & drop an image here, or click to upload
Supports JPEG, PNG, GIF, BMP, WebP formats
Max 10MB, recommend at least 300 DPI resolution
📷 Image Preview
✅ Recognition Result
How to Use
This image-to-text OCR tool is powered by Tesseract.js and runs entirely in your browser. No images are uploaded to any server, ensuring complete privacy. Here's a step-by-step guide:
Upload an Image: Click the upload area or drag and drop an image into the page. The tool supports JPEG, PNG, GIF, BMP, and WebP formats. We recommend images under 10MB with a resolution of at least 300 DPI for optimal results.
Select Language: Choose the recognition language that matches the text in your image. The tool supports over 100 languages including Chinese (Simplified/Traditional), English, Japanese, Korean, French, German, Spanish, Russian, and more. The first time you use a language, the corresponding training data will be downloaded automatically.
Start Recognition: Click the "Start Recognition" button and the tool will process the image and extract the text. A progress indicator shows the real-time status. Processing time depends on image size, text amount, and device performance.
Handle Results: After recognition completes, the extracted text appears in the text box below. You can edit it directly, copy it to your clipboard with the "Copy Result" button, or save it as a text file with the "Download TXT" button. If the results are not ideal, try adjusting the image quality or changing the language setting.
Use Cases
OCR technology has a wide range of applications in daily work and study:
Document Digitization: Convert text from scanned documents, screenshots, or photos into editable digital text for further editing, searching, and archiving. Whether it's contracts, reports, invoices, or business cards, you can quickly convert them to editable text, significantly boosting productivity.
Study Material Organization: Extract text from textbook screenshots, PowerPoint slides, or web page captures to create notes, study materials, and knowledge bases. Students can convert photos of lecture boards or whiteboards into text, saving time on manual transcription.
Image Information Extraction: Extract key text information from social media screenshots, chat message screenshots, or CAPTCHA images. When dealing with large volumes of image-based information, OCR helps quickly locate and extract the content you need.
Multi-language Translation: Recognize text in foreign language images and copy it to translation tools for instant translation, breaking down language barriers. When traveling abroad, you can photograph signs, menus, or labels for quick understanding.
Learn More
Tesseract OCR Engine: Tesseract is an open-source OCR engine originally developed by Hewlett-Packard and now maintained by Google. It supports text recognition in over 100 languages and is considered one of the most accurate open-source OCR engines available. Tesseract.js is the JavaScript port, enabling OCR directly in the browser without server support.
How OCR Works: Optical Character Recognition (OCR) is the process of converting text in images into machine-readable text using optical scanning and pattern recognition. Modern OCR systems typically include preprocessing (noise removal, binarization, skew correction), text detection (locating text regions), character segmentation, and character recognition (pattern matching / deep learning).
Tips for Better Accuracy: 1) Ensure the image is sharp with crisp text edges; 2) Maintain sufficient contrast between text and background; 3) Avoid text tilt - keep it horizontal; 4) Select the correct recognition language; 5) For complex layouts, crop the area you want to recognize before uploading. For printed text, Tesseract typically achieves over 95% accuracy.
Frequently Asked Questions
How accurate is OCR recognition?
OCR accuracy depends on several factors: image clarity, text contrast, font type, and text layout. For clear printed text, accuracy typically reaches 95% or higher. Handwriting or low-quality images will yield lower accuracy. We recommend using high-resolution, high-contrast images for best results.
What languages are supported?
This tool supports over 100 languages including Chinese (Simplified/Traditional), English, Japanese, Korean, French, German, Spanish, Russian, Portuguese, Italian, and Dutch. The first time you use a language, the corresponding training data will be downloaded.
Does my image data get uploaded to a server?
No. All image processing happens locally in your browser using the Tesseract.js engine. Image data is never uploaded to any server, ensuring complete privacy.
Why are there garbled characters or errors in the results?
Possible reasons include: 1) The selected language does not match the text in the image; 2) The image resolution is too low or the text is blurry; 3) Insufficient contrast between text and background; 4) Text is tilted at a steep angle; 5) Artistic fonts or handwriting are used. Try adjusting the image quality or selecting a different language.
Can it recognize handwritten text?
Yes, but handwritten text accuracy is typically lower than printed text. Neat handwriting produces better results, while messy or cursive handwriting may have lower accuracy. We recommend uploading clear images with clean backgrounds for the best recognition results.
What image formats are supported?
JPEG, PNG, GIF, BMP, and WebP formats are supported. We recommend images with a resolution of at least 300 DPI and a file size not exceeding 10MB for the best recognition results.
How do I save the recognition results?
After recognition is complete, click the "Copy Result" button to copy the recognized text to your clipboard, or click "Download TXT" to save the results as a text file. You can also manually select and copy text from the result area.
What affects recognition speed?
Recognition speed mainly depends on: 1) Image size and resolution; 2) Amount of text in the image; 3) Device performance (CPU/GPU); 4) Whether this is the first time using the selected language (language pack needs to be downloaded). Larger images and complex layouts will take longer to process.