An adaptive document recognition system for lettrines

Nhu-Van Nguyen, Mickaël Coustaty, Jean-Marc Ogier

Abstract: In this paper, we propose an approach to interactively propagate annotations representing the historians’ knowledge on a database of lettrine images manually populated by historians (with 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 lettrine database. Our approach is presented together with preliminary experimental results and an illustrative example.