In-vivo differentiation of photo-aged epidermis skin by texture-based classification

Two sets of in vivo female cheek skin epidermis images were analyzed through gray level co-occurrence matrix (GLCM) and fast fourier transform (FFT). One set was derived from women in their 20s and the other from women more than 60 years of age. GLCM was used to evaluate the texture features of the regions of interest within the cheek epidermis, and texture classification was subsequently performed. During texture classification, 25 images (320x240 pixels) in each age set were randomly selected. Three texture features, i.e., energy, contrast, and correlation, were obtained from the skin images and analyzed at four orientations (0 degrees, 45 degrees, 90 degrees, and 135 degrees), accompanied by different distances between two pixels. The textures of the different aging skins were characterized by FFT, which provides the dermatoglyph orientation index. The differences in the textures between the young and old skin samples can be well described by the FFT dermatoglyph orientation index. The texture features varied among the different aging skins, which provide a versatile platform for differentiating the statuses of aging skins.