AdOtsu: An adaptive and parameterless generalization of Otsu's method for document image binarization

Authors:
Reza Farrahi Moghaddam;Mohamed Cheriet
Affiliations:
Synchromedia Laboratory for Multimedia Communication in Telepresence, ícole de Technologie Supérieure, Montreal, QC, Canada H3C 1K3;Synchromedia Laboratory for Multimedia Communication in Telepresence, ícole de Technologie Supérieure, Montreal, QC, Canada H3C 1K3
Venue:
Pattern Recognition
Year:
2012

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Abstract

Adaptive binarization methods play a central role in document image processing. In this work, an adaptive and parameterless generalization of Otsu's 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 DIBCO'09 dataset, with promising results.