Abstract
In this paper, phase congruency features are used to develop a binarization method for degraded documents and manuscripts. Also, Gaussian and median filtering are used in order to improve the final binarized output. Gaussian filter is used for further enhance the output and median filter is applied to remove noises. To detect bleed-through degradation, a feature map based on regional minima is proposed and used. The proposed binarization method provides output binary images with high recall values and competitive precision values. Promising experimental results obtained on the DIBCO’09, H-DIBCO’10 and DIBCO’11 datasets, and this shows the robustness of the proposed binarization method against a large number of different types of degradation.
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Ziaei Nafchi, H., Farrahi Moghaddam, R., Cheriet, M. (2013). Historical Document Binarization Based on Phase Information of Images. In: Park, JI., Kim, J. (eds) Computer Vision - ACCV 2012 Workshops. ACCV 2012. Lecture Notes in Computer Science, vol 7729. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37484-5_1
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DOI: https://doi.org/10.1007/978-3-642-37484-5_1
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