Frequencies decomposition and partial similarities retrieval for ancient handwriting documents compression

This paper presents a new segmentation free approach of partial similarities retrieval in ancient handwritten documents. The method has been developed to improve usual handwritings compression approaches that are not adapted to patrimonial images specificities. We present here the similarities characterization that lies on oriented handwriting shapes decomposition. The frequencies page decomposition realizes a pavement of handwritten regions stored in directional maps where partial similarities are estimated. This decomposition is obtained by a frequencies analysis implying Gabor bank filters with an adequate parameter setting based on the most significant directions of the text. For each map, we compute a similarity graph that reveals redundant shapes and determines a resulting redundancy rate. The resulting graph is the first part of the compression system currently under development.