Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image
- 22 Downloads
In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.
KeywordsVisibility Age spot Freckle Facial color image Subjective evaluation Monte Carlo simulation
This research is partly supported by JSPS Grants-in-Aid for Scientific Research (24560040).
- 1.Wang, L., Jacques, S.L.: Monte Carlo modeling of light transport in multi-layered tissues in standard C. University of Texas, M. D. Anderson Cancer Center (1992)Google Scholar
- 3.Krishnaswamy, A., Baranoski, G.V.G.: A biophysically-based spectral model of light interaction with human skin. Eurographics 23(3), 331–340 (2004)Google Scholar
- 4.Tsumura, N., Kawabuchi, M., Haneishi, H., Miyake, Y.: Mapping pigmentation in human skin from multi-channel visible spectrum image by inverse optical scattering technique. J. Imaging Sci. Technol. 45(5), 444–450 (2000)Google Scholar
- 5.Donner, C., Jensen, H.W.: A spectral BSSRDF for shading human skin. In: EGSR '06 Proceedings of the 17th Eurographics Conference on Rendering Techniques, Nicosia, Cyprus, 26–28 June 2006. doi: 10.2312/EGWR/EGSR06/409-417
- 6.Oregon Medical Laser Center. (1999). http://omlc.org/spectra/hemoglobin/index.html. Accessed 22 Oct 2017
- 7.Jacques, S.L.: Skin optics. Organ Medical Center News. (1998). http://omlc.ogi.edu/news/jan98/skinoptics.html. Accessed 22 Oct 2017
- 9.Hunt, R.W.G., Pointer, M.R.: Measuring colour, 4th edn. Wiley (2011). doi: 10.1002/9781119975595
- 10.Colour Matching Functions. http://cvrl.ioo.ucl.ac.uk/cmfs.htm. Accessed 10 Oct 2017
- 11.Ojima, N., Minami, T., Kawai, M.: Transmittance measurement of cosmetic layer applied on skin by using processing. In: Proceeding of the 3rd scientific conference of the Asian societies of cosmetic scientists, vol. 114 (1997)Google Scholar
- 12.Toyota, S., Fujiwara, I., Hirose, M., Ojima, N., Ogawa-Ochiai, K., Tsumura, N.: Principal component analysis for the whole facial image with pigmentation separation and application to the prediction of facial images at various ages. J. Imaging Sci. Technol. 58(2), 020503-1–020503-11 (2014)CrossRefGoogle Scholar
- 13.Tatsuzawa, Y., Hirose, M., Ojima, N., Ogawa-Ochiai, K., Tsumura, N.: Analyzing the individual relationship between habit of UV protection and melanin pigmentation based on the change of facial images for 7 years. In: Color and imaging conference, Darmstadt, Germany, proceedings, pp 24–28 (2015)Google Scholar