In this paper, we propose a method for handwritten text characterization based on a multiscale and multiresolution drawing analysis. The approach lies on the definition of four complementary handwritten text visual dimensions: the macro and micro orientation (obtained with a frequencies multiscale image analysis), the text linearity (defined by the merge of connected components), the curvature (measured as a multiresolution high profile deformation) and the complexity (expressed as multiscale drawing distribution entropy). Each feature is studied in an evolution graph that can be expressed as a unique handwritten curve signature. It leads to a description in separable writers families having individual visual characteristics. The results are very promising.