Abstract
A fuzzy logic clustering algorithm for classifying a given image into targets and backgrounds is presented. The algorithm forms clusters and is trained without supervision. The clustering is done on the basis of the statistical properties of the set of inputs. The algorithm features an adaptive mechanism for selecting the number of clusters, and it also features an adaptive threshold. The problem of threshold selection is considered, and the convergence of the algorithm is shown. The algorithm also does not require the number of clusters to be known a priori. An example is given to illustrate the application of the algorithm. (Author)