Objective X-ray Image Display Evaluation (OXIDE)
Transportation Security Officers (TSOs) are tasked with exploiting x-ray inspection systems to detect potential threats. To ensure the safety and
security of the traveling public and to ensure efficient operation, TSOs must maintain a 100% probability of detection (Pd) rate while minimizing
screening time and cost. Achieving these objectives requires that x-ray inspection systems operate predictably in accordance with manufacturer
specifications and are calibrated to maximize Pd and reduce screening time. The ASTM X-ray Test Object aims to evaluate image quality (IQ) with
respect to Pd in order to support optimal system calibration. However, the ASTM is fundamentally flawed for several reasons: (1) it is prone to
operator bias; (2) it is not directly representative of real-world operation; (3) it does not quantify the relationship between IQ and Pd; and (4) it cannot
handle moving objects and is therefore ineffective for exploring the use of continuously rotating conveyor belts to speed up the screening process.
To address these concerns, we propose a system for Objective X-ray Image Display Evaluation (OXIDE). OXIDE uses a predictive approach to assess
functional image quality, implemented using a large bank of image features, an array of test kit item detectors, and a regression algorithm which maps
image features to detector performance. To maintain a high Pd, minimize screening time, and improve safety, OXIDE monitors IQ of unseen imagery
during normal operation and cues the operator to potential image degradations during calibration.
Small Business Information at Submission:
Charles River Analytics Inc.
625 Mount Auburn Street Cambridge, MA 02138-4555
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