A novel initialization scheme for the fuzzy c-means algorithm for color clustering

Citations

WEB OF SCIENCE

73
Citations

SCOPUS

96

초록

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. (C) 2003 Elsevier B.V. All rights reserved.

키워드

fuzzy clustering; color clustering; centroid initialization; fuzzy c-means; color membership; IMAGE SEGMENTATION; CLASSIFICATION; SYSTEM; SPACE
제목
A novel initialization scheme for the fuzzy c-means algorithm for color clustering
저자
Kim, Dae-Won; Lee, K.H.; Lee, D.
DOI
10.1016/j.patrec.2003.10.004
발행일
2004-01
유형
Article
저널명
Pattern Recognition Letters
권
25
호
2
페이지
227 ~ 237