Text Line

Text line recognition, a crucial step in document analysis, aims to accurately identify and extract text from images, encompassing both printed and handwritten materials across diverse languages and styles. Current research emphasizes developing robust and generalizable models, employing architectures like transformers and convolutional neural networks within detection-based and segmentation-based frameworks, often incorporating self-training or retrieval augmentation techniques to improve accuracy and efficiency. These advancements are significantly impacting various fields, including historical document processing, business information extraction, and paleography, by enabling automated transcription and structured data extraction from complex and varied sources.