Optical Character Recognition (OCR) is a technology that converts different types of documents, such as scanned paper documents, PDF files, or images captured by a camera, into editable and searchable digital text. OCR systems analyze the shapes and patterns of characters in an image and match them to known letter forms, effectively "reading" printed or handwritten text.
Modern OCR solutions leverage machine learning and deep learning techniques, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to achieve high accuracy even with challenging inputs like handwritten text, distorted fonts, or low-quality scans. Popular OCR tools and services include Tesseract (open source), Google Cloud Vision, Amazon Textract, and ABBYY FineReader.
OCR has wide-ranging applications across industries. In healthcare, it digitizes medical records and prescriptions. In finance, it automates invoice processing and receipt scanning. Legal firms use OCR to make archived documents searchable, while logistics companies scan shipping labels and forms. As AI capabilities continue to advance, OCR is evolving to handle increasingly complex document layouts, multiple languages, and real-time text recognition from video streams.