种子区域生长技术在彩色图像分割中的应用

Application of Seeded Region Growing to Color Image Segmentation

提出一种基于种子区域生长(Seeded Region Growing,SRG)技术的彩色图像分割方法.该算法利用L*a*b*颜色空间的象素与其邻域的颜色差异及相对欧式距离自动选择种子;应用SRG技术由已知的种子生长出初始分割区域;根据融合了颜色空间和邻接关系的区域距离对初始区域进行分级合并.算法克服了传统区域生长方法不能自动选择种子且容易导致过分割的局限性.将新的分割方法应用到彩色图像,并得到与视觉判断相一致的有意义的分割结果.实验结果显示了所提出的方法对于不同自然彩色图像分割的有效性与适应性.

A color image segmentation method is presented based on the SRG method. Seeds can be automatically selected in the L^＊a^＊ b^＊ color space by making use of both color differences and relative Euclidean distances in the new algorithm; the new methods of SRG is used to form the initial segmented regions ; and the initial regions are hierarchically merged based on the region distance defined by the color spatial and adjacent information. The proposed algorithm can overcome the disadvantages of not selecting seeds automatically and leading to the result of over-segmented by the traditional SRG method. And it can be applied to color image segmentation successfully. The meaningful experiment results of color image segmentation hold favorable consistency in terms of human perception and have shown feasibility and effectiveness to various natural color images.