中文摘要：

为克服一般区域生长算法对初始种子点选择以及生长顺序鲁棒性较差的问题,提出了一种鲁棒于生长顺序的彩色图像区域生长算法。首先计算所有像素点的局部颜色直方图以及领域相似性指标（neighbor similarity factor,NSF）;其次通过NSF值建立种子的选取准则、种子的生长准则以及生长的终止准则,对图像进行初分割;最后对未分类点进行重新分类得到最终分割结果。通过与JSEG算法比较发现,该算法的运算时间以及分割准确性具有明显优势。

英文摘要：

A color image segmentation algorithm was proposed under the framework of seeded region growth（SRG）.Compared to existing SRG methods,this method was robust to the selection of initial seed-pixels and the order of region growth.Specifically,there were three main steps： 1） computing a neighborhood based similarity factor（NSF） based on the local color histogram of each pixel;2） building the criteria of seed selection,region growth and region termination principled by NSF;3） assigning labels to those un-segmented pixels for a final segmentation.Experimental results showed the superior performance of our methods in computational complexity and segmentation accuracy to the popular method of JSEG.