@inproceedings{b9a55911acec4120a797a515ae3f41d6,
title = "Binarization of degraded document image using Gaussian Markov random field model",
abstract = "This paper presents a binarization approach to degraded document images, which is based on Gaussian Markov Random Field (GMRF) model. The energy function with the single-site and pair-site clique potential functions is formulated for the GMRF. The parameters of the potential functions are estimated by expectation-maximization (EM) algorithm, without necessity of training process. Experiments on different types of degraded document images with various noise, contrast variation or uneven illumination, have demonstrated the validity of the proposed method.",
keywords = "Binarization, Gaussian Markov Random Field, expectation-maximization",
author = "Shujing Lu and Yue Lu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 4th International Conference on Audio, Language and Image Processing, ICALIP 2014 ; Conference date: 07-07-2014 Through 09-07-2014",
year = "2015",
month = jan,
day = "13",
doi = "10.1109/ICALIP.2014.7009799",
language = "英语",
series = "ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "272--276",
editor = "Wanggen Wan and Fa-Long Luo and Xiaoqing Yu",
booktitle = "ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings",
address = "美国",
}