Optical Character Recognition (OCR) software has been crucial in automating text extraction from scanned documents, images, and PDFs. Some of the most famous OCR software include Tesseract, one of the most popular open-source OCR engines. Tesseract supports multiple languages and is highly customizable, making it suitable for a variety of OCR tasks, from simple text extraction to complex document processing. Another well-known OCR software is Adobe Acrobat Pro DC, which offers powerful OCR capabilities integrated into its PDF management tools. It allows for the conversion of scanned documents into editable text and is commonly used in office and business environments. ABBYY FineReader is another commercial OCR solution that is highly regarded for its accuracy, especially in document conversion and archiving. FineReader supports a wide range of languages and document types, offering both standard OCR and advanced features like layout retention. Google Cloud Vision OCR is an API-based solution provided by Google that offers robust text extraction from images. It leverages Google's AI capabilities to process various document types and integrates easily with cloud-based applications. Finally, Microsoft OCR is part of the Azure Cognitive Services suite, providing OCR for images, documents, and handwriting, and is integrated into Microsoft's cloud environment for developers.
What are the most famous OCR software?

- Retrieval Augmented Generation (RAG) 101
- Information Retrieval 101
- Accelerated Vector Search
- AI & Machine Learning
- The Definitive Guide to Building RAG Apps with LlamaIndex
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
What's the scope of computer vision in AI?
Computer vision plays a crucial role in AI, enabling machines to interpret and analyze visual data, such as images and v
How can multimodal AI help with real-time data processing?
Multimodal AI can significantly improve real-time data processing by integrating and analyzing data from multiple source
What are the common benchmarks used to evaluate zero-shot learning models?
Zero-shot learning (ZSL) models are evaluated using several common benchmarks that help to measure their effectiveness a