Generic scale-space process for handwriting documents analysis
Résumé
This paper presents a generic architecture for handwriting documents
analysis. It covers all analysis steps from the content description of
the document (layout analysis, handwriting shape characterization) to
three dedicated Digital Libraries applications (CBIR
in great ancient documents images database, Paleographical images classification and word
spotting). The generic scale space tool is based on the Curvelets
decomposition of images for the indexation of linear singularities of
handwritten shapes. The proposed scheme for handwritten shape
characterization targets to detect oriented and curved fragments at
different scales: it is used in a first step to extract visual textual
interest regions and secondly to use the Curvelets coefficients in
various ways to satisfy the three designed applications. The complete
implementation scheme is validated with a specific application of word
spotting based on the orientations analysis. The proposed method is
language independent and only visual orientation and appearance
based. In that context, no lexical information nor any other
statistical language models are required. The first proposed tests
for this application are proposed on medieval documents images and on
European 18th century correspondences corpus from the CERPHI.
Precision-recall analysis testifies the relevance of the contribution.