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Keywords:

  • hyper-pigmentation;
  • cross-polarization;
  • fluorescence;
  • CLAHE ;
  • fuzzy c-means algorithm

Background/purpose

Hyperpigmentation is a common skin problem that looks darker than normal skin regions. Accurate evaluation of a hyperpigmented lesion (HPL) is of clinical importance because proper choice of treatment can be dependent on it. This study aimed to differentiate between epidermal and dermal HPLs.

Methods

Cross-polarized color images (CPCIs) and fluorescence color images (FCIs) were acquired from the same facial regions. Contrast-limited adaptive histogram equalization (CLAHE) was employed to enhance the image contrast and a fuzzy c-means algorithm was implemented to extract the HPLs. The HPLs were superimposed to investigate the difference between CPCI and FCI.

Results

The HPL was successfully extracted by applying both CLAHE and fuzzy c-means algorithms. CPCI and FCI resulted in a slightly different HPL, even from the same facial region, indicating a greater percentage area of HPL in FCI than CPCI.

Conclusion

CPCI and FCI may be utilized to differentiate HPLs that exist in different skin layers. Thus, this approach may contribute to the effective treatment of HPLs.