An intelligent skin-color capture method based on fuzzy C-means with applications

Shih Wen Hsiao, Chih Huang Yen, Chu Hsuan Lee

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Consumer behavior is complicated. In the cosmetic market, personal intuition and fashion trends for color selection are guidelines for consumers. A systematic method for female facial skin-color classification and an application in the makeup market are proposed in this study. In this article, face recognition with a large number of images is first discussed. Then, an innovative method to capture color at selected points is presented and complexion-aggregated analysis is performed. This innovative method is an extension of face-recognition theory. Images in RGB format are converted to CIELAB format during data collection and then Fuzzy C-means theory is used to cluster and group the data. The results are classified and grouped in Lab value and RGB index. Two programs are created. The first program, “FaceRGB,” captures color automatically from images. The second program, “ColorFCM,” clusters and groups the skin-color information. The results can be used to assist an expert system in the selection of customized colors during makeup and new-product development.

Original languageEnglish
Pages (from-to)775-787
Number of pages13
JournalColor Research and Application
Issue number6
Publication statusPublished - 2017 Dec

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Chemistry(all)
  • Chemical Engineering(all)


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