1. An automated image annotation method, comprising the steps of: defining a plurality of concepts; providing one or more images associated with each concept; extracting a signature for each image based upon a discrete distribution of visual features associated with that image; constructing a profiling model for each concept by clustering the discrete distributions; storing the profiling models along with one or more textual descriptions of each concept; inputting an image to be annotated; extracting a signature for the image to be annotated based upon a discrete distribution of visual features associated with that image; computing the probability that the image belongs to at least one of the concepts by comparing the discrete distribution of visual features associated with the image to annotated with the stored profiling models and, if the input image belongs to at least one of the concepts; computing the probabilities that the textual descriptions stored with the identified profiling model apply to the image to be annotated; ranking the textual descriptions applied to the image to be annotated; and outputting one or more of the highest-ranked textual descriptions as an annotation of the image to be annotated.