1. A method of classifying objects using volumetric multi-energy CT image data, wherein data from CT and Z (atomic number) images including data from at least one segmented potential threat object are provided, comprising: A. Computing a density histogram for the potential threat object using the CT image data; B. Dividing the density histogram of the potential threat object data into one or more segments; C. Computing the histogram segment features for each segment using the CT and Z image data; D. Classifying each potential threat object into a threat or a non-threat using the computed histogram segment features.