New method for the selection of binarization parameters based on noise features of historical documents

Authors:
Ines Ben Messaoud;Haikal El Abed;Hamid Amiri;Volker Märgner
Affiliations:
Laboratoire des Systèmes et Traitement de Signal, LSTS Ecole Nationale d'Ingénieurs de Tunis, ENIT Tunis, Tunisia;IfN, Technische Universität Braunschweig, Braunschweig, Germany;Laboratoire des Systèmes et Traitement de Signal, LSTS, Ecole Nationale d'Ingénieurs de Tunis, ENIT Tunis, Tunisia;IfN Technische Universität Braunschweig, Braunschweig, Germany
Venue:
Proceedings of the 2011 Joint Workshop on Multilingual OCR and Analytics for Noisy Unstructured Text Data
Year:
2011

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Abstract

Historical documents contain generally different kind of degradations. Due to this degradations the application of methods of noise removal during a preprocessing stage seems to be necessary. Since the noise which, exists in the original document can not be eliminated using a simple noise removal algorithm and it influences the preprocessing result e.g. the binarization, a function of noise detection seems to be necessary. We present in this paper a method for the selection of the input parameters of binarization methods according to the noise type detected in the image. The tests are achieved on benchmarking datasets used at DIBCO 2009 and H-DIBCO 2010. The results returned by the binarization methods using the noise features are promising.