This paper presents a general architecture for ancient handwriting documents content description and retrieval. It is based on the Curvelets decomposition of images for indexing linear singularities of handwritten shapes. As it belongs to the Wavelets family, its representation is used at several scales of details. 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 compose a cross-scale signature for each handwritten analyzed samples. The images description is studied through different kinds of deformations that show the efficiency of the proposition for even degraded and variable handwriting text. The complete implementation scheme is validated with a content based images retrieval (CBIR) application on the medieval database from the IRHT and on the European 18th century correspondences corpus from the CERPHI.