What is OCR?

OCR stands for Optical Character Recognition. It is a technology that converts printed or handwritten text in images (scanned documents, photos, screenshots) into machine-readable text that can be edited, searched, or processed.

Key points:

• Input: images, PDFs, or camera captures containing text.
• Output: plain text or structured text (with layout, fonts, or formatting when advanced).
• How it works (high-level): image preprocessing (deskewing, noise removal), text detection (locating lines/words), character recognition (classifying characters, often using machine learning), and post-processing (spell-checking, language models to fix errors).
• Types: rule-based OCR (pattern matching), modern ML-based OCR (neural networks, convolutional/transformer models) and specialized systems for handwriting (ICR — Intelligent Character Recognition).
• Common uses: digitizing books and documents, automating data entry (invoices, receipts, forms), enabling searchable PDFs, assisting visually impaired users, and extracting text from photos for translation or analysis.
• Limitations: accuracy drops with poor image quality, complex layouts, stylized fonts, handwriting, or multiple languages; requires language-specific models or good preprocessing.

If you want, tell me what kind of documents or images you have and I can recommend specific OCR tools or settings.