hOCR is a format for representing OCR output, including layout information, character confidences, bounding boxes, and style information. It embeds this information invisibly in standard HTML. By building on standard HTML, it automatically inherits well-defined support for most scripts, languages, and common layout options. Furthermore, unlike previous OCR formats, the recognized text and OCR-related information co-exist in the same file and survives editing and manipulation. hOCR markup is independent of the presentation.
OCRopus is a state-of-the-art document analysis and OCR system, featuring pluggable layout analysis, pluggable character recognition, statistical natural language modeling, and multi-lingual capabilities. This server allows you to use the system through your web browser.
Large quantities of historical newspapers are being digitized and OCRd. We describe a framework for processing the OCRd text to identify articles and extract metadata for them. We describe the article schema and provide examples of features that facilitate automatic indexing of them. For this processing, we employ lexical semantics, structural models, and community content. Furthermore, we describe visualization and summarization techniques that can be used to present the extracted events.