Abstract
In this paper, we present a color image segmentation algorithm based on statistical models. A novel deterministic annealing Expectation Maximization (EM) formula is used to estimate the parameters of the Gaussian Mixture Model (GMM), which represents the multi-colored objects statistically. The experimental results show that the proposed deterministic annealing EM provides a global optimal solution for the ML parameter estimation and the image field is segmented efficiently by using the estimates.