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.