Paper
4 September 2009 A novel algorithm for material discrimination using a dual energy imaging system
Kenneth Fu, Dale Ranta, Clark Guest, Pankaj Das
Author Affiliations +
Abstract
Dual energy imaging is a technique whereby an object is scanned with X-rays of two interleaved energies to extract information about the object's atomic composition (Z). This technique is based on the fact that the X-ray absorption coefficient decreases with X-ray energy for low-Z materials, but begins to increase for high-Z materials due to the onset of pair production. Methods using the ratio of the attenuations of high-energy to low-energy images as an indicator of Z value have been proposed by several people. However, the statistical errors associated with the systems make those indicators unreliable. Methods that calculate the probability of high Z encounter a problem of what is the threshold probability to call high Z to minimize both miss and false alarm. We have developed an "adaptive regional masking" method that avoids the predicament of a single threshold. Our method is adaptive because the threshold for determining high Z varies adaptively in different regions on the image. The "mask" refers to the location of objects in the thickness map that mask to possible high-Z regions. Adaptive thresholding improves detection, while masking reduces false alarms. Test results show an increased accuracy of high-Z detection using this approach. In this paper, we discuss the approach and show some sample test results illustrating the effectiveness of the method.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth Fu, Dale Ranta, Clark Guest, and Pankaj Das "A novel algorithm for material discrimination using a dual energy imaging system", Proc. SPIE 7445, Signal and Data Processing of Small Targets 2009, 744513 (4 September 2009); https://doi.org/10.1117/12.825344
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KEYWORDS
X-rays

Signal attenuation

X-ray imaging

Image segmentation

Photons

Imaging systems

Lead

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