Go Toolstack

Client-Side Optical Character Recognition (OCR)

Extract selectable text from photographed documents, receipts, and scans locally in your browser.

Client-Side Optical Character Recognition (OCR)

Extract selectable text from photographed documents, receipts, and scans locally in your browser.

How It Works

1
Select Your File
Choose the file you want to process; your data is processed locally without uploads.
2
Configure Options
Adjust conversion, compression, or processing settings to suit your needs.
3
Process & Download
Run the task client-side in your browser and download the processed result.

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Technical guides, troubleshooting, and best practice walkthroughs

Concept & Knowledge Hub

In-Browser Optical Character Recognition (OCR) & Searchable PDF Studio

In-Browser Optical Character Recognition (OCR) & Searchable PDF Studio detects, transcribes, and transforms visual text from scanned paper documents, smartphone receipts, and multi-page PDFs into fully searchable, selectable dual-layer PDF files directly inside your browser sandbox. Combining Tesseract.js WebAssembly LSTM neural networks with the pdf-lib vector engine and fontkit TrueType embedding, it generates precision text layers matching physical word coordinates with zero server telemetry or remote cloud processing.

Searchable PDF Architecture (The Dual-Layer Sandwich): Traditional OCR conversions either destroy the original scanned document layout by reflowing text into a plain document, or leave the scan as a static, unsearchable bitmap. GoToolstack's Searchable PDF engine constructs a true PDF sandwich: the base layer renders the authentic high-resolution scanned page image, while the overlying layer injects invisible text matching each recognized word's exact spatial coordinates. By setting PDF Text Rendering Mode to 3 Tr (neither stroke nor fill), the text remains 100% invisible to the eye—preserving stamps, signatures, and photos—while remaining completely selectable by cursor drag, indexable by desktop operating system search, and highlightable via Ctrl+F.

Coordinate Geometry & Baseline Mapping: Digital images use a top-left origin (where Y increases downwards), whereas the ISO 32000 PDF standard specifies a bottom-left origin (where Y increases upwards). The engine computes inverted-Y coordinate projections: y_pdf = page_height - y_bottom, adjusting vertical alignment to the typography baseline (y_baseline = y_pdf + 0.18 * box_height). To prevent selection highlight drift caused by variable glyph widths across proportional fonts, the engine calculates horizontal glyph squeeze ratios using the standard PDF Tz operator (scale = (box_width / natural_width) * 100), ensuring the cursor highlight perfectly hugs the printed word on the scan.

Reading Order, Columns & User Corrections: In two-column documents (such as academic journals and legal briefs), words are clustered by horizontal centroid intervals so left-hand columns read continuously top-to-bottom before advancing to the right-hand column. When users correct misrecognized characters in the monospace text editor, the engine maps edited tokens directly back into coordinate boxes, guaranteeing that corrected text appears in the downloaded PDF.

Document Element Scope & Legal Limitations: Because client-side OCR rasterizes incoming pages to preserve visual layout fidelity, original interactive PDF form fields (AcroForms/XFA), clickable hyperlinks, and cryptographic digital signatures (PKCS#7/PAdES) are flattened into the image. Cryptographic signatures are invalidated when underlying streams are rewritten. Furthermore, this initial release does not claim PDF/A archival compliance (ISO 19005) or PDF/UA accessibility tagging (ISO 14289). For complex bidirectional and Indic scripts (Arabic, Hebrew, Hindi), where LTR PDF streams limit invisible layer alignment, the studio provides an honest 'Image-Only PDF' or clean 'TXT' export alternative.

Best Practices & Essential Guidelines

  • Focus on actual pixel detail rather than 300 DPI metadata: ensure lowercase letters measure at least 20–30 pixels in height on the canvas.
  • Use Otsu binarization for clean typed print, or contrast stretch with gamma adjustment for uneven lighting or scanner grain.
  • Review flagged low-confidence words using the interactive word chips to correct potential character substitutions before exporting.
  • When exporting Searchable PDFs, select 'Auto' font mode to embed NotoSans TrueType for Turkish, Cyrillic, and European accented characters.

Frequently Asked Questions (FAQ)

What is a Searchable PDF sandwich and how does it work?
A Searchable PDF combines the original scanned image with an invisible text layer positioned directly over each printed word. Using PDF Text Rendering Mode 3 (3 Tr), text can be selected, searched with Ctrl+F, and copied, while preserving the exact original visual appearance of the document.
How does the tool map image pixel coordinates to PDF coordinates?
The engine maps top-left image pixel coordinates to bottom-left PDF point space, computing baseline offsets and applying PDF horizontal scaling (Tz operators) to ensure text highlights precisely match scanned word boundaries.
Are my manual text edits included in the exported Searchable PDF?
Yes. Any edits made in the monospace text editor are synchronized with the underlying word bounding boxes, allowing you to fix OCR typos before generating the final searchable document.
Are digital signatures and interactive forms preserved from source PDFs?
No. The OCR process rasterizes source pages to ensure visual consistency and embeds new searchable text layers. Original cryptographic signatures, interactive form inputs, and hyperlinks are flattened and not preserved.