Improving weapon detection in single energy X-ray images through pseudocoloring

This paper describes a series of linear and nonlinear pseudocoloring maps designed and applied to single energy X-ray luggage scans to assist airport screeners in identifying and detecting threat items, particularly hard to see low-density weapons in luggage. Considerations of the psychological and physiological processing involved in the human perception of color as well as the effects of using various color models, such as the RGB and HSI models, were explored. Original grayscale data, various enhanced images, and segmented scenes were used as input to the various color mapping schemes designed in this research. A highly interactive user-friendly graphical interface and a portable test were developed and used in a performance evaluation study involving a population of actual federal airport screeners. The study proved the advantages of using color over gray level data and also allowed the ranking of color maps and selection of the best performing color schemes. Rate improvements in weapon detection of up to 97% were achieved through the use of color.