Abstract
Regarding the missing texture details in the texture extraction process of Tenglong Yuan blue and white, illumination is unequal. A meta blue and white texture extraction method based on adaptive gamma correction and K-means clustering segmentation coupling algorithm has been proposed. Combining the characteristics of Tenglong Yuan blue and white texture, using grayscale transformation to adjust the brightness of blue and white images, image contrast has been enhanced. Design Gaussian filter, weighted average multiscale Gaussian convolution, constructing 2D gamma convolutions for adaptive gamma correction, enhance the texture of Tenglong Yuan blue and white, the details in the blue and white texture of Tenglong Yuan are richer and more prominent. K-means clustering segmentation algorithm based on Lab space, implementing color segmentation of blue and white images, helps to segment the blue and white texture of Tenglong Yuan. Verification indicates that this method can effectively improve the contrast of blue and white texture; the accuracy rate of Tenglong Yuan blue and white texture segmentation reaches 95%. Effectively improving the accuracy of texture extraction for blue and white elements, the protection and inheritance of Yuan blue and white cultural relics are promoted.
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References
Hoo, Q., Wang, X., Yuan, F., et al.: Microstructure and coloring mechanism of iron spots on bluish white porcelain from Jingdezhen of the Song Dynasty. J. Eur. Ceram. Soc. 41(6), 3816–3822 (2021)
Luo, M., Zhang, M., Yan, W., et al.: X-ray absorption spectroscopy study of synthetic cobalt blue pigments similar to Kangxi blue and white porcelain. J. Am. Ceram. Soc. 101(5), 2130–2136 (2018)
Fischer, C., Hsieh, E.: Export Chinese blue-and-white porcelain: compositional analysis and sourcing using non-invasive portable XRF and reflectance spectroscopy. J. Archaeol. Sci. 80, 14–26 (2017)
Figueiredo, M.O., Silva, T.P., Veiga, J.P.: A XANES study of cobalt speciation state in blue-and-white glazes from 16th to 17th century Chinese porcelains. J. Electron Spectrosc. Relat. Phenom. 185(3–4), 97–102 (2012)
Lin, H., Yao, M., Tao, Y., et al.: A flexible smart monitoring system for the conservation of textile relics. Adv. Func. Mater. 31(48), 2106088 (2021)
Dang, Y., Luo, X., Chang, B., et al.: Local attachment ventilation system for the unearthed relic preservation area within site museum. Sustain. Cities Soc. 77, 103537 (2022)
Tsirikoglou, A., Eilertsen, G., Unger, J.: A survey of image synthesis methods for visual machine learning. Comput. Graphics Forum 39(6), 426–451 (2020)
Li, C., Huang, Y., Li, H., et al.: A weak supervision machine vision detection method based on artificial defect simulation. Knowledge-Based Syst. 208, 106466 (2020)
Li, C., Chen, H., Li, X., et al.: A review for cervical histopathology image analysis using machine vision approaches. Artif. Intell. Rev. 53, 4821–4862 (2020)
Liu, Y., Jia, Z., Liu, W., et al.: An improved image acquisition method for measuring hot forgings using machine vision. Sens. Actuators, A 238, 369–378 (2016)
Jiang, Y., Hu, K., Zhang, X., et al.: A saturation channel detection method for surface defects of silicon nitride bearing rollers based on adaptive gamma correction-edge threshold segmentation coupling algorithm. Mater. Today Commun. 36, 106397 (2023)
Liao, D., Yin, M., Luo, H., et al.: Machine vision system based on a coupled image segmentation algorithm for surface-defect detection of a Si3N4bearing roller. J. Opt. Soc. Am. A 39, 571–579 (2022)
Lu, B., He, Y., Wang, H.: Stereo disparity optimization with depth change constraint based on a continuous video. Displays 69, 102073 (2021)
Fiorucci, M., Khoroshiltseva, M., Pontil, M., et al.: Machine learning for cultural heritage: a survey. Pattern Recogn. Lett. 133, 102–108 (2020)
Li, P., Liang, J., Zhang, M.: A degradation model for simultaneous brightness and sharpness enhancement of low-light image. Signal Processing 189, 108298 (2021)
Veluchamy, M., Subramani, B.: Fuzzy dissimilarity color histogram equalization for contrast enhancement and color correction. Appl. Soft Comput. 89, 106077 (2020)
Miao, Y., Li, S., Wang, L., et al.: A single plant segmentation method of maize point cloud based on Euclidean clustering and K-means clustering. Comput. Electron. Agric. 210, 107951 (2023)
Reza, M.N., Na, I.S., Baek, S.W., et al.: Rice yield estimation based on K-means clustering with graph-cut segmentation using low-altitude UAV images. Biosys. Eng. 177, 109–121 (2019)
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Xiang Ning, Nanxing Wu, and Rumeng Zhang contributed to the work equally and should be regarded as co-first authors.
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Ning, X., Wu, N., Zhang, R. et al. Tenglong Yuan blue and white texture extraction method based on adaptive gamma correction and K-means clustering segmentation coupled algorithm. J Aust Ceram Soc 60, 1–11 (2024). https://doi.org/10.1007/s41779-023-00981-w
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DOI: https://doi.org/10.1007/s41779-023-00981-w