A Facial-Skin Condition Classification System in Wavelet Domain

This paper describes a facial-skin condition evaluation system based on cosmetician´s suggestions to let the users realize their facial-skin conditions. Two kinds of features are extracted from the captured skin image. Four parameters of sub-band information of the gray part of a color skin image in wavelet domain are used as the first kind of features. The contrast, inverse difference moment, deviation information in the gray-value histogram, and the entropy of the co-occurrence matrix information are calculated as the second kind of features. The fuzzy rule extraction on the first-kind features is sued to distinguish the oily skin group from the others. The fuzzy c-means process with the second-kind features is used to classify the neutral skin and the dry skin. In the experiments, the classified results are compared with the cosmeticians´ results, and the correct rates are 100% for the first test group of 30 test images and 92.8% for the second test group of 14 images.