2013 12th International Conference on Document Analysis and Recognition (2013)
Washington, DC, USA USA
Aug. 25, 2013 to Aug. 28, 2013
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2013.67
This paper deals with cultural heritage preservation and ancient document indexing. In the management of historical documents, ancient images are described using semantic information, often manually annotated by historians. In this paper, we propose an approach to interactively propagate the historians' knowledge to a database of drop caps images manually populated by historians with drop caps image annotations. Based on a novel document indexing processing scheme which combines the use of the Zipf law and the use of bag of patterns, our approach extends the Bag of Words model to represent the knowledge by visual features through relevance feedback. Then annotation propagation is automatically performed to propagate knowledge to the drop caps image database. In this article, our approach is presented together with preliminary experimental results and an illustrative example.
Visualization, Indexing, Semantics, Libraries, Image color analysis, Analytical models
N. Nguyen, M. Coustaty, A. Boucher and J. Ogier, "Interactive Knowledge Learning for Ancient Images," 2013 12th International Conference on Document Analysis and Recognition(ICDAR), Washington, DC, USA USA, 2013, pp. 300-304.