How to Extract Text from Images Using OCR.
Free online OCR guide.
Learn how to convert images to text using free online OCR. Extract text from screenshots, scanned documents, photos, and more — all in your browser, no uploads to any server.
What is OCR and Why Use It?
Optical Character Recognition (OCR) is technology that converts different types of documents — scanned paper documents, PDFs, or images captured by a camera — into editable and searchable text. Instead of manually typing text from an image, OCR automates the process in seconds. ImageFree uses Tesseract.js, a powerful open-source OCR engine that runs entirely in your browser — your image never leaves your device.
How to Extract Text from Images in 3 Steps
Step 1: Upload Your Image
Navigate to the OCR Converter page and upload your image. You can drag and drop a file or click to browse. The tool supports JPG, PNG, WebP, BMP, and other common image formats.
Step 2: Extract Text
Click the "Extract Text" button. The OCR engine processes your image entirely in your browser using WebAssembly — nothing is uploaded to any server. The processing time depends on the image size and your device speed. A progress indicator shows the recognition status. The tool is optimized for English text but supports multiple languages.
Step 3: Copy or Download
Once the text is extracted, it appears in a text box. You can copy it to your clipboard with one click, or select and copy specific parts. The extracted text can be pasted into any document, email, or application.
Best Practices for Accurate OCR
- Use high-resolution images: The clearer the text, the more accurate the recognition.
- Ensure good contrast: Dark text on a light background produces the best results.
- Avoid skewed angles: Straight-on captures with minimal perspective distortion work best.
- Clean images: Remove smudges, stains, or marks that could confuse the OCR engine.
- Proper lighting: Avoid shadows across the text for clean recognition.
Common OCR Use Cases
- Digitizing printed documents: Convert physical documents into editable digital text.
- Extracting text from screenshots: Capture text from videos, presentations, or web pages.
- Processing business cards: Digitize contact information from business card photos.
- Product label information: Extract ingredient lists, barcodes, or product details from packaging.
- Academic research: Convert scanned book pages or research papers into searchable text.