A Cellular Telephone-Based Application for Skin-Grading to Support Cosmetic Sales

  • Hironori Hiraishi
  • Fumio Mizoguchi


We have developed a sales-support system for door-to-door sales of cosmetics based on a system called Skin-Expert, a skin-image grading service that includes analysis and diagnosis. Skin-Expert analyzes a customer's current skin quality from a picture of the skin. Several parameters are extracted by image processing, and the skin grading is done by rules generated by data mining from a baseline of grades given by human skin-care experts. Communication with the Skin-Expert is through a cellular telephone with a camera, using e-mail software and a Web browser. Salespeople photograph the customer's skin using the camera in a standard cellular telephone and then send an e-mail message that includes the picture as an attachment to our analysis system. Other parameters associated with the customer (for example, age and gender) are included in the body of the message. The picture is analyzed by our skin-grading system, and the results are made available as a page in HTML format on a customer-accessible Web site. An e-mail is sent when the results are available, usually within minutes. Salespeople check the results by using a Web browser on their cellular telephones. The output not only provides a grading result but also gives recommendations for the care and cosmetics that are most suitable for the customer. Our system integrates cellular communication, Web technology, computer analysis, data mining, and an expert system. Though salespeople use only a cellular telephone with very little computing power as the front end, they can take advantage of intelligent services such as computer grading and data mining. The salespeople do not need to think about what is running in the background, and there is no requirement that end users have any special hardware.
How to Cite
Hiraishi, H., & Mizoguchi, F. (2004). A Cellular Telephone-Based Application for Skin-Grading to Support Cosmetic Sales. AI Magazine, 25(3), 17. https://doi.org/10.1609/aimag.v25i3.1773