clustering an african hairstyle dataset using pca and k-means
Teffo Phomolo Nicrocia Owolawi Pius Adewale Pholo Moanda Diana
The adoption of digital transformation was not expressed in building an
African face shape classifier. In this paper, an approach is presented that
uses k-means to classify African women images. African women rely on beauty
standards recommendations, personal preference, or the newest trends in
hairstyles to decide on the appropriate hairstyle for them. In this paper, an
approach is presented that uses K-means clustering to classify African women's
images. In order to identify potential facial clusters, Haarcascade is used for
feature-based training, and K-means clustering is applied for image
classification.