OCR PDF: Extract Text from Scanned Documents in Your Browser
OCR PDF: Extract Text from Scanned Documents in Your Browser
Scanned PDFs contain images of pages, not embedded text. You can see the text visually, but you cannot search it, copy it, or edit it — the computer treats each page as a photograph. OCR (Optical Character Recognition) solves this by analyzing the page images and recognizing the text characters, producing searchable, editable text output.
How Browser-Based OCR Works
The tool uses Tesseract.js, a JavaScript port of the Tesseract OCR engine, to perform character recognition entirely in your browser. The process has three stages:
1. PDF rendering. PDF.js loads the PDF and renders each page to a canvas element at high resolution, creating a detailed image of the page.
2. Character recognition. Tesseract.js analyzes each page image, identifying text characters by their visual patterns. It uses language models to improve accuracy by recognizing common letter combinations and words.
3. Output generation. The recognized text is assembled into the chosen output format — plain text (.txt) or a searchable PDF with the text content on each page.
Everything runs client-side. The scanned PDF is loaded into your browser, the OCR processing happens on your device's CPU, and the output is generated locally. No document is uploaded to any server.
What Affects OCR Accuracy
Scan quality. High-resolution, high-contrast scans produce the best results. Documents scanned at 150 DPI or higher with clear, dark text on a white background are ideal. Low-resolution scans, blurry images, or faded text produce more errors.
Document condition. Clean, undamaged pages convert well. Pages with stains, creases, or handwritten annotations produce more errors because the OCR engine may misinterpret marks as characters.
Font and layout. Standard printed fonts in simple layouts are the easiest to recognize. Decorative fonts, unusual typefaces, or complex multi-column layouts increase error rates.
Language. The tool uses the English language model. Documents in other languages will not recognize correctly because the language model expects English character patterns and word shapes.
Processing Time
OCR is CPU-intensive. Each page typically takes 10-30 seconds depending on the amount of text and image complexity. A 10-page document may take several minutes. The tool shows a progress indicator so you can track which page is being processed.
The processing happens on your device, so faster computers complete OCR more quickly. On mobile devices or older hardware, expect longer processing times.
Output Formats
Plain text (.txt). All recognized text is extracted into a single text file with page break markers between pages. This is the simplest format — useful for copying text into other applications, searching, or feeding into text-to-speech tools.
Searchable PDF. A new PDF is created with the recognized text placed on each page at the original page dimensions. The text is selectable and searchable within the PDF. The output contains text only — the original page images are not included.
Best Practices for Clean Results
Use high-quality scans. If you are scanning documents specifically for OCR, scan at 200-300 DPI in grayscale or color (not black and white, which can lose detail). Ensure the pages are flat and well-lit.
Clean up the scans first. If the scanned pages have borders, punch holes, or other artifacts, crop them out before running OCR. Non-text elements can confuse the recognition engine.
Proofread the output. OCR is not perfect. Always review the extracted text for errors, especially in critical documents like legal or financial records. Technical terms, proper nouns, and numbers are the most common sources of errors.
Process one document at a time. Since OCR is CPU-intensive, processing one document at a time gives the best results. Running multiple OCR operations simultaneously will slow down your browser.
Try the OCR PDF tool to extract text from your scanned documents.