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Improved analysis for skin color separation based on independent component analysis

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Abstract

The conventional skin color separation method suffers from the severe limitation that the input skin image must have no shading component and must have substantial variation in the pigment density distribution, simultaneously. We therefore propose an improved method, which uses two input skin images instead of one. In this improved method, one input image has no shading component and the other has substantial variation in pigment density distribution. To verify the effect of our method, we took images of four subjects and separated them into pigment components. We then compared the independence evaluation value of the separated signals extracted using our method and that of the conventional method. The results show that we obtain separated signals that have a better independence evaluation value by our method than by the conventional method.

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Acknowledgements

We thank Edanz Group (http://www.edanzediting.com/ac) for editing a draft of this manuscript.

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Authors and Affiliations

  1. Ricoh Company, Ltd., Tokyo, Japan

    Satomi Tanaka

  2. Department of Imaging Sciences, Graduate School of Engineering, Chiba University, Chiba, Japan

    Satomi Tanaka & Norimichi Tsumura

Authors
  1. Satomi Tanaka
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  2. Norimichi Tsumura
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Correspondence to Satomi Tanaka.

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Tanaka, S., Tsumura, N. Improved analysis for skin color separation based on independent component analysis. Artif Life Robotics 25, 159–166 (2020). https://doi.org/10.1007/s10015-019-00572-8

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  • DOI: https://doi.org/10.1007/s10015-019-00572-8

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