Although most histogram-based image segmentation methods rely on the identification of a good threshold, we show that thresholding is not mandatory. Instead, we propose the association of grades of membership to each individual pixel, in order to perform probabilistic relaxation in the image space (which realizes some kind of regularization) and finally to obtain the segmented image through defuzzy fication of the relaxed grades of membership.