Objective X-ray Image Display Evaluation (OXIDE)

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: HSHQDC-13-C-00073
Agency Tracking Number: DHS SBIR-2012.2-H-SB012.2-003-0001-II
Amount: $749,394.67
Phase: Phase II
Program: SBIR
Awards Year: 2013
Solitcitation Year: 2012
Solitcitation Topic Code: H-SB012.2-003
Solitcitation Number: DHS SBIR-2012.2
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, 02138-4555
Duns: 115243701
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Ross Eaton
 (617) 491-3474
 reaton@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
N/A
Abstract
Transportation Security Officers (TSOs) are tasked with exploiting X-ray inspection systems to detect potential threats. To ensure efficient operation and the safety of the traveling public, TSOs must maintain a 100% probability of detection (Pd) while minimizing screening time. To achieve these objectives, X-ray inspection systems must operate in accordance with manufacturer specifications, and be calibrated to maximize Pd and reduce screening time. The ASTM X-ray Test Object aims to evaluate image quality (IQ) with respect to Pd 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 designed, developed, and demonstrated a prototype for Objective X-ray Image Display Evaluation (OXIDE). OXIDE uses a predictive approach to assess functional IQ during normal operation, producing a single General Image Score that can cue the operator to potential image degradations. The system leverages our existing object detection and IQ technologies to achieve robust and purely objective IQ evaluation for X-ray screening systems. The Phase I prototype accurately predicts functional IQ on real X-ray imagery that has been randomly degraded, corresponding well to a human's qualitative interpretation of relative image quality, and demonstrating the feasibility of our predictive IQ assessment approach.

* information listed above is at the time of submission.

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