Open AccessCross‐evaluation of facial hyperpigmented lesions based on fluorescence color image and cross‐polarized color image
Author(s) -
Kim Eunji,
Kim Dongyoun,
Choi Eung H.,
Jung Byungjo
Publication year - 2013
Publication title -
skin research and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.521
H-Index - 69
eISSN - 1600-0846
pISSN - 0909-752X
DOI - 10.1111/j.1600-0846.2012.00665.x
Subject(s) - adaptive histogram equalization , contrast (vision) , hyperpigmentation , histogram equalization , artificial intelligence , computer science , histogram , pattern recognition (psychology) , medicine , dermatology , image (mathematics)
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 HPL s. Methods Cross‐polarized color images ( CPCI s) and fluorescence color images ( FCI s) 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 HPL s. The HPL s 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 HPL s that exist in different skin layers. Thus, this approach may contribute to the effective treatment of HPL s.