An adaptive document recognition system for lettrines

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 th...

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Bibliographic Details
Published in:International journal on document analysis and recognition 2020-06, Vol.23 (2), p.115-128
Main Authors: Nguyen, Nhu-Van, Coustaty, Mickael, Ogier, Jean-Marc
Format: Article
Language:English
Subjects:
Adaptive systems
Annotations
Artificial Intelligence
Computer Science
Computer Vision and Pattern Recognition
Digital Libraries
Document and Text Processing
Historians
Image Processing and Computer Vision
Knowledge representation
Original Paper
Pattern Recognition
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Summary: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.
ISSN:1433-2833
1433-2825
DOI:10.1007/s10032-019-00346-9