Image segmentation is a difficult task. These years, researchers have proposed many segmentation methods based on
Evolutionary Algorithms, but most of them used Evolutionary Algorithms to optimize the parameters of an existing
segmentation algorithm. This paper tries to use the Evolutionary Algorithms to segment images expecting to explore a
new way of image segmentation. The method described in the paper pre-segments the image by Watersheds and then
merges it by Immune Clonal Algorithm (ICA). To implement the task, several operators are proposed such as the DC
operator, the Proportional Creation of the First generation operator, and fitness function based on JND and average gray
value. In the end, the proposed method is compared with another method using GA. The experiments show that the
method is effective and the work is significant.