A novel initialization scheme for the fuzzy c-means algorithm for color clustering ?
A novel initialization scheme for the fuzzy c-means (FCM) algorithm is proposed for the color clustering problem. Given a set of color points, the proposed initialization scheme extracts the most vivid and distinguishable colors, referred to here as the dominant colors. The color points closest to these dominant colors are selected as the initial centroids in the FCM calculations. To obtain the dominant colors and their closest color points, we introduce reference colors and define a fuzzy membership model between a color point and a reference color. The effectiveness and reliability of the proposed method is demonstrated through various color clustering examples.
fuzzy c-means color clustering fuzzy clustering centroid initialization color membership