  The interactive image segmentation algorithm can provide an intelligent ways
to understand the intention of user input. Many interactive methods have the
problem of that ask for large number of user input. To efficient produce
intuitive segmentation under limited user input is important for industrial
application. In this paper, we reveal a positive feedback system on image
segmentation to show the pixels of self-learning. Two approaches, iterative
random walks and boundary random walks, are proposed for segmentation
potential, which is the key step in feedback system. Experiment results on
image segmentation indicates that proposed algorithms can obtain more efficient
input to random walks. And higher segmentation performance can be obtained by
applying the iterative boundary random walks algorithm.
