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Open Access Feature Selection for Material Identification in Spectral CT

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Detecting materials of interest in containers using X-ray measurements is a critical problem in aviation security. Conventional X-ray systems obtain single- or dual-energy measurements, which are subsequently processed using computed tomography (CT) to obtain estimates of attenuation properties of different regions. Recently, novel detectors enable the measurement of the X-ray transmission intensities on multiple energy bands, leading to the use of spectral CT to construct additional properties of regions to assist in material identification. In this paper, we discuss the problem of material classification using spectral CT. We introduce a new basis representation which can accurately represent energy-dependent X-ray transmission characteristics in a few dimensions, and propose a class of reconstruction techniques for obtaining features of different regions. We illustrate the advantages of our approach over alternative approaches using different basis representations as well as CT reconstructions in each energy band using simulated spectral CT experiments. Our results illustrate that there are significant advantages to using our basis representation in both detection and material classification performance, particularly in the presence of complex materials or mixtures involving atoms with high atomic number.

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Keywords: CT IMAGE RECOGNITION; EXPLOSIVE DETECTION; MATERIAL CLASSIFICATION; PHOTO-ELECTRIC AND COMPTON DECOMPOSITION; SPARSE REPRESENTATION OF SIGNALS

Document Type: Research Article

Publication date: January 1, 2018

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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