Title :
Quantification of pigmentation in human skin images
Author :
Hao Gong ; Desvignes, M.
Author_Institution :
GIPSA-Lab., Grenoble Inst. of Technol., Grenoble, France
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
In this paper, we propose and compare four different approaches for quantification of hemoglobin and melanin in skin color images. The first method is to extract erythema/melanin indices based on skin absorbance theories. The second method is based on independent component analysis (ICA) assuming that hemoglobin and melanin absorbance spectra are independent. The third method is based on non-negative matrix factorization (NMF) with multiplicative update algorithm. The fourth method is a Beer-Lambert law based model-fitting technique. Quantitative evaluation through graph-cut segmentation on melanoma indicates that model-fitting method outperforms the other three methods.
Keywords :
feature extraction; image colour analysis; independent component analysis; matrix algebra; medical image processing; proteins; skin; Beer-Lambert law; ICA; NMF; graph cut segmentation; hemoglobin quantification; hemoglobinabsorbance spectra; human skin image pigmentation; independent component analysis; melanin absorbance spectra; melanin quantification; nonnegative matrix factorization; skin absorbance theories; skin color images; Covariance matrix; Equations; Image color analysis; Malignant tumors; Mathematical model; Matrix decomposition; Skin; ICA; NMF; graph cuts; hemoglobin; melanin; model-fitting; skin pigmentation;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6467494