Research on the Identification of Modern Ceramic Ornaments Based on Wireless Network-Guided Artificial Intelligence Model and the Communication Strategy of Chinese Ceramic Culture and Creative Industry in Southeast Asia

Authors

  • Zhenhua Zhong Azman Hashim International Business School (AHIBS)，Universiti Teknologi Malaysia, Kuala Lumpur (Graduate School), Malaysia
  • Nor Hidayati Zakaria Azman Hashim International Business School (AHIBS)，Universiti Teknologi Malaysia, Kuala Lumpur (Graduate School), Malaysia
  • Kaidi Zhang Jingdezhen Vocational University of Art, Jingdezhen City, Jiangxi Province, China
  • Peiyao Chen Jingdezhen Vocational University of Art, Jingdezhen City, Jiangxi Province, China

Keywords:

Artificial intelligence (AI), Artificial Neural Network (ANN), Canny Edge Detection (CED), Chinese ceramic, DGLSSC, Hough circular transformation (HCT), MATLAB, PCA-TS, Unconfined Weed Optimization Algorithm (UWOA)

Abstract

The functional and artistic qualities of ancient Chinese ceramic are desired across the globe. Recognizing the cultural interchange, wherein the identification for ancient ceramic is a critical feature, necessitates a thorough examination of ancient ceramic. Artificial intelligence (AI) has been used to assist in the recognition of ancient ceramics in this work. This research proposes a novel Unconfined Weed Optimization Algorithm (UWOA). Initially, the Chinese ceramic datasets are gathered and are pre-processed using canny edge detection (CED). Then the features of the pre-processed dataset are extracted using Hough circular transformation (HCT) that can be properly performed by employing both direct grey level symmetric similarity calculation (DGLSSC) and principal component analysis based texture symmetric similarity detection (PCA-TS) techniques. The extracted data are feed to the prediction process of ceramic properties using Artificial Neural Network (ANN) in AI. To optimize the ANN, the proposed approach can be utilized. Finally, the performances of the proposed approach are examined and the outcomes are depicted using the MATLAB tool.

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References

L. Lei, and Z. Shouli, “Analysis of the relationship between modeling and decoration in ceramic design.” in Proc. Int. Conf. Econ. Manage. Cultural Ind. (ICEMCI), pp. 868–871,. Dec. 2019

P. Ballirano, C. De Vito, L. Medeghini, S. Mignardi, V. Ferrini, P. Matthiae, D. Bersani, and P. P. Lottici, “A combined use of optical microscopy, X-ray powder diffraction and micro-Raman spectroscopy for the characterization of ancient ceramic from Ebla (Syria)”, Ceram. Int., vol. 40, no. 10, pp.16409–16419, 2014.

M. Emami, Y. Sakali, C. Pritzel, and R. Trettin, “Deep inside the ceramic texture: A microscopic–chemical approach to the phase transition via partial-sintering processes in ancient ceramic matrices”. J. microsc. Ultrastruct., vol 4, no. 1, pp. 11–19, 2016.

I. Karatasios, A. Hein, N. S. Müller, P. Triantafyllides, and V. Kilikoglou, “Technological insights into the ancient ceramic beehive production of Agathonisi island, Greece.” Appl. Clay Sci., vol. 82, pp. 37–43, 2013.

K. Liu, T. Wu, D. L. Bourell, Y. Tan, J. Wang, M. He, H. Sun, Y. Shi, and J. Chen, “Laser additive manufacturing and homogeneous densification of complicated shape SiC ceramic parts.” Ceram. Int., vol. 44, no. 17, pp. 21067–21075, 2018.

L. M. Bresciani, A. Manes, and M. Giglio, “An analytical model for ballistic impacts against ceramic tiles.” Ceram. Int., vol. 44, no. 17, pp. 21249–21261, 2018.

T. Mu, F. Wang, X. Wang, and H. Luo, “Research on ancient ceramic identification by artificial intelligence.” Ceram. Int., vol. 45, no. 14, pp. 18140–18146, 2019.

A. M. Hunt and R. J. Speakman, “Portable XRF analysis of archaeological sediments and ceramics.” J. Archaeol. Sci., vol 53, pp. 626–638, 2015.

E. Frahm, “Ceramic studies using portable XRF: From experimental tempered ceramics to imports and imitations at Tell Mozan, Syria.” J Archaeol. Sci., vol. 90, pp. 12–38, 2018.

V. Panchuk, I. Yaroshenko, A. Legin, V. Semenov, and D. Kirsanov, “Application of chemometric methods to XRF-data–A tutorial review.” Anal. Chim. Acta, vol. 1040, pp. 19–32, 2018.

M. L. Gualandi, G. Gattiglia, and F. Anichini, “An open system for collection and automatic recognition of pottery through neural network algorithms.” Heritage, vol. 4, no. 1, pp. 140–159, 2021.

D. Crevier, AI: The tumultuous history of the search for artificial intelligence, Basic Books, Inc. 1993.

A. Di Ludovico and M. Ramazzotti, “Reconstructing lexicography in glyptic art: Structural relations between the Akkadian age and the Ur III period.”in Proceedings of the 51st Rencontre Assyriologique Internationale, Held at the Oriental Institute of the University of Chicago, pp. 263–280, 2005.

P. Carr, “Archaeology and the application of artificial intelligence: Case studies on use-wear analysis of prehistoric flint tools.” (Reviews). Am. Antiq.,vol. 67, no. 2, pp. 376–377, 2002.

L. V. D. Maaten, P. Boon, G. Lange, H. Paijmans, and E. Postma, Computer vision and machine learning for archaeology, 2007.

H. Sun, M. Liu, L. Li, L. Yan, Y. Zhou, and X. Feng, “A new classification method of ancient Chinese ceramics based on machine learning and component analysis.” Ceram. Int., vol. 46, no. 6, pp. 8104–8110, 2020.

Overall structure of the research dataset

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Published

19.12.2022

How to Cite

Zhenhua Zhong, Nor Hidayati Zakaria, Kaidi Zhang, & Peiyao Chen. (2022). Research on the Identification of Modern Ceramic Ornaments Based on Wireless Network-Guided Artificial Intelligence Model and the Communication Strategy of Chinese Ceramic Culture and Creative Industry in Southeast Asia. International Journal of Intelligent Systems and Applications in Engineering, 10(2s), 43–48. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2359

Issue

Vol. 10 No. 2s (2022)

Section

Research Article

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Copyright (c) 2022 Zhenhua Zhong, Nor Hidayati Zakaria, Kaidi Zhang, Peiyao Chen

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