AdOtsu: An adaptive and parameterless generalization of Otsuʹs method for document image binarization

Adaptive binarization methods play a central role in document image processing. In this work, an adaptive and parameterless generalization of Otsuʹs method is presented. The adaptiveness is obtained by combining grid-based modeling and the estimated background map. The parameterless behavior is achieved by automatically estimating the document parameters, such as the average stroke width and the average line height. The proposed method is extended using a multiscale framework, and has been applied on various datasets, including the DIBCOʹ09 dataset, with promising results.