Abstract
Energy dispersive x-ray diffraction spectra are obtained from numerous volume elements within an object. A feature set such as a set of cepstrum coefficients is extracted from each spectrum and classified by a trained classifier such as a neural network to provide an indication of whether or not contraband such as explosives is present in the volume element. Indications for adjacent volume elements are evaluated in conjunction with one another, as by an erosion process, to suppress isolated indications and thereby suppress false alarms.