A Divisive Hierarchical k-means based Algorihtm for Image Segmentation

摘要：

In this paper we present a divisive hierarchical method for the analysis and segmentation of visual images. The proposed method is based on the use of the k-means method embedded in a recursive algorithm to obtain a clustering at each node of the hierarchy. The recursive algorithm determines automatically at each node a good estimate of the parameter k (the number of clusters in the k-means algorithm) based on relevant statistics. We have made several experiments with different kinds of images obtaining encouraging results showing that the method can be used effectively not only for automatic image segmentation but also for image analysis and, even more, data mining.

作者: Jos(e) Antonio Mart(I)n H. Javier Montero Javier Y(a)(n)ez Daniel G(o)mez

作者单位: Informatics and Computing Universidad Complutense de Madrid, Spain 28040 MathematicsUniversidad Complutense de Madrid, Spain 28040 Statistics Universidad Complutense de Madrid, Spain 28040

会议类型: 国际会议

会议名称: The 2010 International Conference on Intelligent Systems and Knowledge Engineering(第五届智能系统与知识工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 300-304

在线出版日期: 2010-11-15（万方平台首次上网日期，不代表论文的发表时间）