A distributed environment with rough set theory based image processing approach for analysis of facial disorders for better cosmetic product recommendation

Abstract

Producers and Consumers are getting progressively open to the use of cosmetic beauty care products. This can be found in them utilizing an assortment of regular Cosmetic resources and materials. This reality is additionally upheld by the pattern of natural and health awareness. This experience can be found inside both the Producers and Consumers behavior. Fast development of beauty care products industry, the improvement of new advances and the style for wonderful and youthful skin caused that fashion became basics for present day society. As the growth of cosmetic industry increases, the number of cases related to side effects of the products are also getting increased. According to Central Drugs Standard Control Organization, nearly 8% of the customers are facing side effects because of unsuitable products. There is no proper model used by the cosmetic product producers to suggest suitable cosmetic product to the customers. To reach the requirements of the various customers, the cosmetic industry needs to manage enormous features of skin, extract from the face images of the customers, out of which not many are required to recognize the skin issues and fundamental item stimulation. The proposed work mainly concentrates on designing a model for better cosmetic product suggestions to the customers to reduce the side effects and to have a healthy and shining skin. Advanced image handling and examination of clinical face images can successfully strengthen medical diagnosis with important plans including automatic prediction and analysis, image segmentation and estimation of obvious features in images. Rough set theory is one of numerous techniques that can be utilized to break down and analyze images, less regular than progressively customary strategies for probability, statistics and set theory. In this manuscript a distributed environment with rough set theory based image processing method is used for analysis of facial disorders for better cosmetic product recommendation that cannot cause any harm or disorder to the customer with use of cosmetic products that improves the safety of the customers. The proposed model performs product recommendations based on local and global features based on the customer locality. The proposed method is compared with the traditional methods and the results show that the proposed method exhibits better accuracy in prediction of skin disorders in cosmetic industry.