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A Facial-Skin Condition Classification System Using Texture and Fuzzy C-Means Technologies

This paper describes a facial-skin condition classification system based on cosmeticians' suggestions to let the users realize their facial-skin conditions. Two kinds of features are extracted from the captured skin image. 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 firs kind of features. Four parameters in Wavelet domain are used as the second kind of features. A 2-stage fuzzy c-means process is used to classify these 2 kinds of features into 3 groups: the oily skin, neutral skin, and the dry skin. In the two experiments, the classified results are compared with the cosmeticians' results, and the average correct rate is 93%.