ocr

Optical Character Recognition (OCR) extracts text from images and documents using AI. **Modern OCR capabilities**: Deep learning achieves 99%+ accuracy on printed text, handles multiple fonts/languages, extracts structured data from documents. **Technologies**: Tesseract (Google, open source, 100+ languages), EasyOCR (PyTorch-based, 80+ languages), PaddleOCR (excellent multilingual), Document AI services (AWS Textract, Google Document AI, Azure Form Recognizer). **Beyond basic OCR**: Document understanding extracts tables, forms, hierarchies. Named entity recognition identifies key information. Layout analysis preserves structure. **Challenges**: Handwriting recognition still difficult, degraded documents need preprocessing, complex layouts require specialized models. **Preprocessing pipeline**: Deskewing, denoising, binarization, contrast enhancement improve accuracy. **Use cases**: Digitizing archives, automating data entry, invoice processing, receipt scanning, accessibility (screen readers), searchable PDF creation. **Best practices**: Use appropriate resolution (300 DPI+), clean images before processing, validate critical extractions, train custom models for domain-specific documents.