OCR guide
How to Extract Text from Images Using OCR (Image → Text)
If you have scanned documents, photos of printed pages or screenshots of text, re-typing everything is slow and error-prone. This guide shows how to use WebSauda OCR to extract text directly from images in your browser.
What is OCR?
OCR stands for Optical Character Recognition. It is a technology that analyses the shapes of letters in an image and converts them into digital text. Once converted, you can copy, edit or search that text like any other document.
Use cases for image to text
- Converting scanned mark sheets or certificates into editable text.
- Extracting content from book pages or study material.
- Copying text from screenshots of websites or apps.
- Digitising printed office circulars or notices.
Step-by-step: extract text with WebSauda OCR
- Open the WebSauda OCR (Image → Text) tool.
- Upload an image file (JPG, PNG, WebP or a scanned document).
- Wait while the OCR engine reads the image and extracts text. Progress may take a little time for large or complex pages.
- Once finished, review the recognised text, copy it to your clipboard or download it into a text file.
Tips for better OCR accuracy
- Use clear, in-focus images with good lighting.
- Ensure the text is not too small or heavily tilted.
- Prefer printed text; handwriting recognition is always harder.
- If possible, crop unnecessary borders or background before running OCR on the image.
Is browser-based OCR safe?
WebSauda OCR uses a client-side engine (Tesseract.js), which means the heavy work happens directly in your browser. Images do not need to be permanently stored or reused on a server, which is better for privacy-sensitive documents.
Related tools
- PDF Merge — combine scanned pages into a single PDF after extracting key text.
- PDF Compress — reduce the size of scanned PDFs before uploading them to portals.