Segmentation-based retrieval of document images from diverse collections

We describe a methodology for retrieving document images from large extremely diverse collections. First we perform content extraction, that is the location and measurement of regions containing handwriting, machineprinted text, photographs, blank space, etc, in documents represented as bilevel, greylevel, or color images. Recent experiments have shown that even modest per-pixel content classification accuracies can support usefully high recall and precision rates (of, e.g., 80

• Type: Conference
• Year: 2008
• Where: DRR
• Authors: Michael A. Moll, Henry S. Baird
• Keywords: Content Extraction, Data Set, Document Analysis, DRR 2008, Modest Per-pixel Content