Handwriting Similarities as Features for the Characterization of Writer's Style Invariants and Image Compression

In this paper, we propose a new approach of similarity retrieval in ancient handwritten documents. Similarities are retrieved on shape fragments which can be analysed according to different granularities (from the grapheme to the character size) depending on the handwriting quality, regularity and sharpness. The approach is based on a “segmentation free” methodology which considers the image with all frequencies and Gray levels. The method has been applied for two purposes: to establish the basis of a new handwritings compression approach based on handwritten images specificities and to show that only shape fragments can efficiently be used for writer characterization. We present here the global methodology for the similarities characterization which lies on an oriented handwriting shapes decomposition. First results for data compression and writer characterization are very encouraging in a field where there is no anterior work.