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fil/.ai-rulez/domains/ocr-integration/DOMAIN.md
Henrik Jess Nielsen b4c07d3693
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2026-06-01 23:40:55 +02:00

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description
description
OCR backend integration and image processing
  • Multiple backends: Tesseract (C FFI via leptonica/tesseract-sys), PaddleOCR (ONNX Runtime), Python backends (EasyOCR, Surya) via FFI
  • Backend selection: priority-based with fallback — Tesseract default, PaddleOCR for CJK, Python backends as fallback
  • Image preprocessing: deskew, binarization, noise removal, contrast enhancement — applied before OCR
  • PSM modes: configurable page segmentation (single block, single line, sparse text) per use case
  • Table detection: identify table regions → cell extraction → row/column reconstruction → Markdown table output
  • hOCR: parse Tesseract hOCR output for word-level bounding boxes, confidence scores, reading order
  • Language management: auto-detect document language, load appropriate Tesseract traineddata, support multi-language documents
  • Caching: cache OCR results by image hash + backend + language + PSM mode
  • Confidence tracking: per-word and per-page confidence scores, flag low-confidence regions for review