A prototype document image analysis system for technical journals

Gobbledoc, a system providing remote access to stored documents, which is based on syntactic document analysis and optical character recognition (OCR), is discussed. In Gobbledoc, image processing, document analysis, and OCR operations take place in batch mode when the documents are acquired. The document image acquisition process and the knowledge base that must be entered into the system to process a family of page images are described. The process by which the X-Y tree data structure converts a 2-D page-segmentation problem into a series of 1-D string-parsing problems that can be tackled using conventional compiler tools is also described. Syntactic analysis is used in Gobbledoc to divide each page into labeled rectangular blocks. Blocks labeled text are converted by OCR to obtain a secondary (ASCII) document representation. Since such symbolic files are better suited for computerized search than for human access to the document content and because too many visual layout clues are lost in the OCR process (including some special characters), Gobbledoc preserves the original block images for human browsing. Storage, networking, and display issues specific to document images are also discussed.<>