Color imaging systems can be useful and reliable for evaluating the severity of rosacea, in addition to biophysical parameter assessment. The combination of these two analytical methods enabled objective and quantitative evaluation of the severity of rosacea.

The proposed method in this study shows that the skin surface can be quantitatively evaluated by the similarity with ground truth. We also propose a method to diagnose and manage individual skin condition using a mobile camera in real life.

The proposed RPF is a promising technology because it allows for any stereo image to be filtered without the risk of losing the original roughness. In addition, the algorithm runs automatically for any given stereo skin image with relation to the disparity parameter λ, and the roughness parameters R or R are given priority. Although this method has been optimized by graph-cut disparity map building, it can be extended to other disparity map building methods because the parameter k is determined by actual roughness R data that can be obtained by simple measurement.