Abstract: An algorithm for determination of the number of modes in a gray-level image histogram is presented in this paper. The hypothesis is that the image histogram's pdf is approached by a mixture of Gaussians. Then, the algorithm tries to estimate the number of components in the mixture, which is an important parameter when using the maximum likelihood technique to estimate the remaining of parameters of the mixture. The algorithm is divided into two parts. First, initial clustering using the k-means algorithm is performed. This allows to estimate the centers of each cluster. Second, a novel algorithm, denoted łElimination of False Clusters˛ (EFC) based on the Gaussian characteristics tries to suppress clusters which have no corresponding modes in the histogram. The algorithm has been validated on both artificial and real histograms.