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Skin Pigment Recognition using Projective Hemoglobin- Melanin Coordinate Measurements

  • Yang, Liu (Dept. of IT Convergence and Application Engineering, Pukyong National Univ.) ;
  • Lee, Suk-Hwan (Dept. of Information Security, Tongmyong Univ.) ;
  • Kwon, Seong-Geun (Dept. of Electronics Engineering, KyungIl Univ.) ;
  • Song, Ha-Joo (Dept. of IT Convergence and Application Engineering, Pukyong National Univ.) ;
  • Kwon, Ki-Ryong (Dept. of IT Convergence and Application Eng., Pukyong National Univ.)
  • Received : 2015.07.24
  • Accepted : 2016.05.09
  • Published : 2016.11.01

Abstract

The detection of skin pigment is crucial in the diagnosis of skin diseases and in the evaluation of medical cosmetics and hairdressing. Accuracy in the detection is a basis for the prompt cure of skin diseases. This study presents a method to recognize and measure human skin pigment using Hemoglobin-Melanin (HM) coordinate. The proposed method extracts the skin area through a Gaussian skin-color model estimated from statistical analysis and decomposes the skin area into two pigments of hemoglobin and melanin using an Independent Component Analysis (ICA) algorithm. Then, we divide the two-dimensional (2D) HM coordinate into rectangular bins and compute the location histograms of hemoglobin and melanin for all the bins. We label the skin pigment of hemoglobin, melanin, and normal skin on all bins according to the Bayesian classifier. These bin-based HM projective histograms can quantify the skin pigment and compute the standard deviation on the total quantification of skin pigments surrounding normal skin. We tested our scheme using images taken under different illumination conditions. Several cosmetic coverings were used to test the performance of the proposed method. The experimental results show that the proposed method can detect skin pigments with more accuracy and evaluate cosmetic covering effects more effectively than conventional methods.

Keywords

Acknowledgement

Grant : Development of Media Application Framework based on Multi-modality which enables Personal Media Reconstruction

Supported by : IITP, National Research Foundation of Korea(NRF), IITP(Institute for Information & communications Technology Promotion)

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