This paper reviews some recent advances in the theory and applications of morphological image analysis. Regarding applications, we show how the morphological filters can be used to provide simple and systematic algorithms for image processing and analysis tasks as diverse as nonlinear image filtering, noise suppression, edge detection, region filling, skeletonization, coding, shape representation, smoothing, and recognition. Regarding theory, we summarize the representation of a large class of translation-invariant nonlinear filters (including morphological, median, order-statistic, and shape recognition filters) as a minimal combination of morphological erosions or dilations; these results provide new realizations of these filters and lead to a unified image algebra.