In high dimension space, many conventional clustering algorithms do not work well in effectiveness and efficiency, especially for image data set. For example, k-means is widely used in image clustering especially visual clustering. But its drawback such as long clustering time and high memory cost seriously deteriorates feasibility in incremental large image set. To improve the feasibility, we ...