@InProceedings{ICCS2020_GMM,
author="Krupi{\'{n}}ski, Robert
and Lech, Piotr
and Okarma, Krzysztof",
editor="Krzhizhanovskaya, Valeria V.
and Z{\'a}vodszky, G{\'a}bor
and Lees, Michael H.
and Dongarra, Jack J.
and Sloot, Peter M. A.
and Brissos, S{\'e}rgio
and Teixeira, Jo{\~a}o",
title="Improved Two-Step Binarization of Degraded Document Images Based on Gaussian Mixture Model",
booktitle="Computational Science -- ICCS 2020",
year="2020",
publisher="Springer International Publishing",
address="Cham",
pages="467--480",
abstract="Image binarization is one of the most relevant preprocessing operations influencing the results of further image analysis conducted for many purposes. During this step a significant loss of information occurs and the use of inappropriate thresholding methods may cause difficulties in further shape analysis or even make it impossible to recognize different shapes of objects or characters. Some of the most typical applications utilizing the analysis of binary images are Optical Character Recognition (OCR) and Optical Mark Recognition (OMR), which may also be applied for unevenly illuminated natural images, as well as for challenging degraded historical document images, considered as typical benchmarking tools for image binarization algorithms.",
isbn="978-3-030-50426-7"
}