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Skin Reflectance Reconstruction Based on the Polynomial Regression Model

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Image and Graphics Technologies and Applications (IGTA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1480))

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Abstract

Skin spectral reflectance has applications in numerous medical fields including the diagnosis and treatment of cutaneous disorders and the provision of maxillofacial soft tissue prostheses. This paper describes the polynomial model based on the least square (LS) method for skin spectral reflectance from RGB. Furthermore, this paper uses the real human skin data, which makes our results more practical. The performance is evaluated by the mean, maximum and standard deviation of color difference values under other sets of light sources. The values of standard deviation of root mean square (RMS) errors and goodness of fit coefficient (GFC) between the reproduced and the actual spectra were also calculated. Results are compared with the Xiao’s method. All metrics show that the proposed method leads to considerable improvements in comparison with the Xiao’s method.

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Authors and Affiliations

  1. School of Science, Shenyang Jianzhu University, Shenyang, 110168, Liaoning, China

    Long Ma & Yingying Zhu

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  1. Long Ma
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  2. Yingying Zhu
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Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Yongtian Wang

  2. Beijing Institute of Technology, Beijing, China

    Weitao Song

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Ma, L., Zhu, Y. (2021). Skin Reflectance Reconstruction Based on the Polynomial Regression Model. In: Wang, Y., Song, W. (eds) Image and Graphics Technologies and Applications. IGTA 2021. Communications in Computer and Information Science, vol 1480. Springer, Singapore. https://doi.org/10.1007/978-981-16-7189-0_2

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  • DOI: https://doi.org/10.1007/978-981-16-7189-0_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7188-3

  • Online ISBN: 978-981-16-7189-0

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