OCR
Optical Character Recognition
Technology that converts images of text into machine-readable text data.
Technical Detail
OCR works by analyzing pixel patterns in scanned or photographed text. Modern OCR engines like Tesseract use neural networks (LSTM architectures) trained on millions of character samples across hundreds of languages. The process involves binarization, skew correction, line segmentation, word segmentation, and character classification. Post-processing with language models and dictionaries improves accuracy beyond raw character recognition, typically achieving 95-99% accuracy on clean printed text.
Example
```javascript
// OCR: PDF manipulation example
import { PDFDocument } from 'pdf-lib';
const pdfDoc = await PDFDocument.load(fileBytes);
const pages = pdfDoc.getPages();
console.log(`Pages: ${pages.length}`);
```
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