Preparation of Papers in 2-column Format

In this paper, a hybrid approach that is based on a genetic algorithm (GA) is proposed for automatic multilevel image thresholding. In the proposed approach, the Gaussian kernel smoothing is used to estimate the number of classes in an image. Since the parameter estimation in the method is typically a nonlinear optimization problem, the parameters used in the mixture of Gaussian functions that give the best fit to the processed histogram are determined using GA. In experiments, synthetic data and real image were processed by the proposed approach to evaluate the thresholding performance. The experimental results to confirm the proposed approach are also included.