PDF & Image to Text OCR Extractor

Understanding how text is stored inside a PDF determines the optimal extraction strategy: • Digital Vector PDFs: Generated by software like Microsoft Word or LaTeX. Text glyphs are encoded alongside Unicode mappings and coordinate positioning matrices. Our Local Extraction engine uses Mozilla PDF.js to directly read these native character streams without raster OCR, though font mappings, reading order and mixed image content can affect completeness. • Scanned Image PDFs & Photos: Contain flat bitmap pictures without underlying character coordinates. These require rasterization followed by Optical Character Recognition (OCR), where neural or statistical filters identify glyph shapes, baseline angles, and word boundaries.

This static release uses two local extraction paths: 1. Fast Local Text Layer (Mozilla PDF.js): Inspects native document streams inside browser memory. If selectable text exists, it is parsed directly. 2. Local Scanned OCR (Tesseract.js WebAssembly): If a page is purely an image, the page is rendered onto an in-memory HTML5 Canvas and processed by Tesseract's LSTM model compiled to WebAssembly. The selected document is not uploaded for this operation; engine and language assets can download on first use.

When scanning documents for OCR: • Resolution: Ensure scanned images are at least 150 to 300 DPI. Resolutions below 100 DPI merge letter stems (such as 'rn' into 'm'). • Skew & Rotation: Use MultiPDF Doc's Organize tool to straighten rotated pages before running OCR. • Lighting: Ensure uniform contrast without harsh drop-shadows on smartphone receipts or contracts.

The local pipeline inspects each page for extractable text. Pages with native text use PDF.js; pages without text are rendered for Tesseract OCR. The output follows the PDF's original page order. A short digital line is still useful text and should not be discarded merely because it has fewer than an arbitrary number of characters. Mixed documents need particular review. A page can contain digital text plus an image with additional writing; a native-text pass does not necessarily recognize the writing inside that image. The tool's result is therefore a transcript to check, not a guaranteed complete reconstruction of every visual element. Compare names, amounts, dates and table columns with the original before relying on the output for another task.

On first use, the local OCR engine may download its worker, WebAssembly resources and English language data. These requests do not contain your selected document, but they mean that opening the page alone is not a guarantee of immediate offline OCR. Processing can take longer for scanned pages than native text. Keep the tab open and allow the sequential page work to finish. This static release has no Cloud OCR endpoint. PDF text extraction, scanned-page recognition and transcript editing all execute locally. The English worker, language data and compatible WebAssembly variants are served from this website. Downloads may take time on a slow connection, but they do not include your selected document. OCR supports printed English; handwriting, other languages and dense tables may be inaccurate. If a browser cannot process the file, split it into smaller batches or use a suitable desktop OCR application. For mixed pages containing both selectable text and a scanned image, choose “OCR every PDF page” to rasterize and recognize each page. This takes longer and may introduce recognition errors into text that was already selectable. Compare the automatic and full-page results with the original before deciding which transcript to keep. Cancel stops the active extraction; it does not modify your source document. Engine initialization or page recognition that exceeds the bounded wait reports a clear error so you can retry with a smaller scan. Inputs are limited to 100MB, 200 PDF pages and 20 million rendered pixels per scanned page. These safeguards are ceilings rather than promises that every file below them will succeed on every device.

Search filters the displayed transcript to matching lines. While that filter is active, the text area is read-only so an edit cannot accidentally replace the full transcript with only the visible matches. Clear the search before editing the complete text. Copy and download actions use the full current transcript rather than treating a filtered view as the only result. Clipboard access depends on browser permissions and a suitable page context. If copying is blocked, select the text manually or use the text download. OCR errors are reported separately from successful extracted content so a service failure is not mistaken for a document's words. Retain the original file alongside a verified transcript. Plain text does not preserve page geometry, signatures or every table relationship, even when its words appear correct.