Facial perception is what usually human beings do during their daily communications. They may adjust and change the method or contents of the interaction based on this perception. One of the most probable places of this process is during the personalized advertising that is highly under consideration nowadays. Here as a sample of this kind of systems it is tried to propose a system named ?Discerning Advisor? for suggesting clothing fashion considering matching colors with the perception of skin color from the face. This is a considerable point by the fashion designers and advisors which the system will be trained by their knowledge.

For this purpose a comprehensive study has been done on the human skin color model and its variations around the world and among different races. A neural network based skin detector was designed and trained to extract the skin area of the images automatically. It was applied on a large dataset of digital images containing 1000 faces of peoples of almost all races from 23 cities around the world. Calculating indicator color for each individual gave the ability of analysis of distribution and fuzzy-clustering the skin color. Finally the clustering result was used in classification of the skin color that can be matched with the suggested colors from the fashion designers.