OCR Engine

Optical Character Recognition (OCR) engines aim to automatically extract text from images, a crucial task with broad applications. Current research emphasizes improving accuracy and robustness in challenging scenarios, such as handling diverse fonts, complex layouts, degraded images (e.g., historical documents), and multiple languages, often employing deep learning models like transformers and convolutional neural networks. These advancements are vital for digitizing vast archives, improving accessibility of historical texts, and enabling efficient information extraction from various sources, including scanned documents and images from cameras.