Biological inspired tools for patrimonial handwriting denoising and categorization

In this paper, we propose a global segmentation free methodology for patrimonial documents denoising, handwriting characterization and categorization that are based on biological inspired approaches. We widely used here the spectral domain of handwritten images by frequency decompositions: Hermite transforms and Gabor bank filters. Handwritten pages are described by a multiscale signature that is based on orientation features and that is at the basis of a similarity measure. The current results of handwriting categorization and indexing are very promising and show that it is possible to analyze handwritten drawings without any a priori graphemes segmentation.