New Binarization Approach Based on Text Block Extraction

Document analysis and recognition systems include, usually, several levels, annotation, preprocessing, segmentation, feature extraction, classification and post-processing. Each level may be dependent on or independent from the other levels. The presence of noise in images can affect the performance of the entire system. This noise can be introduced by the digitization step or from the document itself. In this paper, we present a new binarization approach based on a combination between a preprocessing step and a localization step. The aim of the present approach is the application of binarization algorithms on selected objects-of-interest. The evaluation of the developed approach is performed using two benchmarking datasets from the last two document binarization contests (DIBCO 2009 and H-DIBCO 2010). It shows very promising results.