This paper proposes an approach to process drop cap images - images of decorated letter that begin chapters of old documents that are preserved in libraries, museums - in the domain of characterization, classification and indexing of old documents. The originality of our proposal is based on the fact that we do not try to extract the letter of drop caps but to classify the drop caps according to period, author and style. The drop caps are characterized by using relevant visual features such as length, thickness, orientation, complexity and change of direction on their primitive elements: strokes. The purpose of this approach is to efficiently extract information embedded in the drop caps for the classification and the indexing of old documents. These new visual features based on bags of strokes are more easily calculable and generally applicable than texture or shape features. Experiments based on characterization, classification and indexing phases demonstrate the performance of our propositions and the advances that they represent in terms of content-based drop caps retrieval.
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