Image segmentation plays an important part in the areas of multimedia

image processing and computer vision. In the paper

the authors propose an image segmentation approach based on an entropy measurer. Specifically

the image segmentation entropy (ISE) is defined to describe the information of an image region. We further prove that the image after segmentation have the minimum ISE

if the image is correctly partitioned. Then

the image segmentation problem is cast into an optimization problem which minimizes ISE. Finally

we use the iterative graph cut approach (IGCA) to solve the optimization problem. The experiments provided in the paper show that our ISE based segmentation approach works well.