Image to Text (OCR)

Optical Character Recognition (OCR) is a technology that converts images of text — whether from scanned documents, photographs, screenshots, or PDFs — into machine-readable, editable text. Modern OCR engines use neural networks trained on millions of text samples to recognize characters with high accuracy across fonts, sizes, and languages. Browser-based OCR, like this tool, uses WebAssembly-compiled engines (such as Tesseract.js) that run entirely on your device, providing both speed and privacy.

Millions of documents exist only as images or physical paper — receipts, contracts, handwritten notes, whiteboards, signs, and historical records. OCR makes this content searchable, editable, and accessible. Students photograph lecture slides and extract the text for notes. Businesses digitize paper invoices and receipts for accounting. Researchers convert scanned historical documents into searchable archives. Accessibility tools use OCR to read text aloud from images for visually impaired users. The ability to extract text from images is a fundamental productivity tool.

Image quality is the primary factor: higher resolution, good lighting, and sharp focus dramatically improve results. Contrast between text and background matters — dark text on a light background works best. Font size should be at least 10-12 points in the original document. Skewed or rotated text reduces accuracy — straighten images before processing. Handwritten text is significantly harder than printed text and requires specialized models. Complex layouts with columns, tables, and mixed content require advanced segmentation. Clean, single-column printed text achieves 99%+ accuracy.

Crop your image to include only the text region — background clutter reduces accuracy. Ensure the image is well-lit and in focus. If photographing a document, use a flat surface and avoid shadows. For multi-page documents, process one page at a time for best results. After extraction, always review the output for errors, especially in numbers, proper nouns, and special characters. If accuracy is low, try increasing image resolution or improving contrast before re-processing.