Abstract

The Global cosmetic industry borders are expanding everyday with new product launches and new packaging for old products. To cater the needs of the diverse customers, the industry has to deal with enormous features of skin, extracted from the face images of the customers, out of which few are required to identify the skin problems and necessary product rejuvenation. This paper proposes data mining techniques to meet these challenges in the cosmetic industry. The proposed approach is based on rough set theory, for discretizing the skin data which is of continuous valued in nature, feature selection using quick reducts and categorization of skin problems using rough clustering technique.

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