We present a new algorithm for the efficient estimation of piecewise parametric models for image segmentation. This algorithm permits the simultaneous estimation of: the number of models, the parameters for each model and the regions where each model is applicable. It is based on Bayesian estimation theory, and is theoretically justified by the use of a specific cost function that decreases at every iteration and by a new model for the posterior marginal distributions, which is amenable to the use of fast computational methods.