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A novel automatic image segmentation method for Chinese literati paintings using multi-view fuzzy clustering technology

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Abstract

Under the background of contemporary cultural protection and dynamic inheritance, the interpretation and re-expression of the artistic connotations of Chinese literati paintings have become the main direction of heritage research. Digital technology and multimedia expression have become important means of cultural expression and transmission. Most Chinese literati paintings are ink paintings, and the particularity of ink painting makes it difficult to decompose and extract the screen content by simple means, which has caused difficulties in digitization, re-expression, and public interpretation to some extent. To solve this problem, a new robust multi-view (M-V) fuzzy clustering algorithm is proposed for image segmentation of Chinese literati paintings to achieve effective decomposition and extraction of ancient paintings. Through the effective decomposition and extraction of literati paintings, the electronic and digital transformation and preservation of literati paintings can be realized. This kind of preservation method, more than traditional scanning, can preserve the artistry of literati paintings, which is of great value for the re-expression and dissemination of cultural heritage. Experiments on noise-added Brodatz texture images show that the proposed algorithm is insensitive to noise and has good robustness. Experiments on real Chinese literati paintings show that the proposed algorithm can effectively segment literati paintings and further realize their decomposition and extraction.

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Acknowledgements

This work was supported in part by the Cultural Science Research of Jiangsu Province under Grant 18YB27, by Jiangsu University Philosophy and Social Science Research Fund under Grant 2018SJA0808, by the National Key R&D Program of China under Grant 2017YFB0202300, by the National Natural Science Foundation of China under Grants 61702225 and 61772241, by the Natural Science Foundation of Jiangsu Province under Grant BK20160187, by the 2018 Six Talent Peaks Project of Jiangsu Province under Grant XYDXX-127, by the Science and Technology demonstration project of social development of Wuxi under Grant WX18IVJN002, and by the Jiangsu Committee of Health under Grant H2018071.

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Authors and Affiliations

  1. School of Digital Media, Jiangnan University, 1800 Lihu Avenue, Wuxi, Jiangsu, 214122, People’s Republic of China

    Jie Zhang, Yizhang Jiang & Yuan Liu

  2. Jiangsu Key Laboratory of Media Design and Software Technology, 1800 Lihu Avenue, Wuxi, Jiangsu, 214122, People’s Republic of China

    Jie Zhang & Yizhang Jiang

  3. Wuxi Museum, 100 Zhongshu Road, Wuxi, Jiangsu, 214023, People’s Republic of China

    Yintao Zhou

  4. Changshu No. 1 People’s Hospital, Changshu, Jiangsu, 215500, People’s Republic of China

    Kaijian Xia

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  1. Jie Zhang
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  2. Yintao Zhou
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  3. Kaijian Xia
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  4. Yizhang Jiang
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  5. Yuan Liu
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Correspondence to Yuan Liu.

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Zhang, J., Zhou, Y., Xia, K. et al. A novel automatic image segmentation method for Chinese literati paintings using multi-view fuzzy clustering technology. Multimedia Systems 26, 37–51 (2020). https://doi.org/10.1007/s00530-019-00627-7

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