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Binarization Chinese Rubbing Images Using Gaussian Mixture Model

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Intelligent Computing Theories and Methodologies (ICIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9225))

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Abstract

Rubbings are important components of ancient Chinese books, and are the main source for people to learn, study, and research history. Image segmentation plays a crucial role in extracting useful information and characteristics of Chinese character from the rubbing images. In this paper, binarization using a Gaussian Mixture Model (GMM) with 2 components for representation of background and foreground distribution in a Chinese rubbing image has been proposed. To model the likelihood of each pixel belonging to foreground or background, a foreground and background color model are learned from three color bands samples that using RGB color space. The standard Expectation-Maximisation (EM) algorithm had been used to estimate the GMM parameters. Experimental results on real rubbing images validate the effectiveness of the model when working with Chinese rubbing images.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61472173), the grants from the Science and Technology Planning Project of Jiangxi Province of China, No. 20111BBG70032-2.

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Authors and Affiliations

  1. Nanchang Institute of Technology, College of Mechanical and Electrical Engineering, Nanchang, 330099, Jiangxi, China

    Zhi-Kai Huang, Fang Wang & Jun-Mei Xi

  2. School of Mechanical and Engineering, Harbin Institute of Technology, Harbin, 150080, Heilongjiang, China

    Han Huang

Authors
  1. Zhi-Kai Huang
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  2. Fang Wang
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  3. Jun-Mei Xi
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  4. Han Huang
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Corresponding author

Correspondence to Zhi-Kai Huang .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytecnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

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Huang, ZK., Wang, F., Xi, JM., Huang, H. (2015). Binarization Chinese Rubbing Images Using Gaussian Mixture Model. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9225. Springer, Cham. https://doi.org/10.1007/978-3-319-22180-9_46

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  • DOI: https://doi.org/10.1007/978-3-319-22180-9_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22179-3

  • Online ISBN: 978-3-319-22180-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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