PROCEEDINGS ARTICLE | May 18, 2012
Proc. SPIE. 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI
KEYWORDS: Image fusion, Backscatter, Image segmentation, Image processing, X-rays, Feature extraction, Lung, Image classification, Brain-machine interfaces, X-ray imaging
Current aviation security relies heavily on personnel screening using X-ray backscatter systems or other advanced
imaging technologies. Passenger privacy concerns and screening times can be reduced through the use of low-dose twosided
X-ray backscatter (Bx) systems, which also have the ability to collect transmission (Tx) X-ray. Bx images reveal
objects placed on the body, such as contraband and security threats, as well as anatomical features at or close to the
surface, such as lungs cavities and bones. While the quality of the transmission images is lower than medical imagery
due to the low X-ray dose, Tx images can be of significant value in interpreting features in the Bx images, such as lung
cavities, which can cause false alarms in automated threat detection (ATD) algorithms. Here we demonstrate an ATD
processing chain fusing both Tx and BX images. The approach employs automatically extracted fiducial points on the
body and localized active contour methods to segments lungs in acquired Tx and Bx images. Additionally, we derive
metrics from the Tx image can be related to the probability of observing internal body structure in the Bx image. The
combined use of Tx and Bx data can enable improved overall system performance.
