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Objective X-ray Image Display Evaluation (OXIDE)

Award Information

Department of Homeland Security
Award ID:
Program Year/Program:
2012 / SBIR
Agency Tracking Number:
DHS SBIR-2012.2-H-SB012.2-003-0001-I
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Charles River Analytics Inc.
MA Cambridge, MA 02138-4555
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2012
Title: Objective X-ray Image Display Evaluation (OXIDE)
Agency: DHS
Contract: HSHQDC-12-C-00077
Award Amount: $99,993.20


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.

Principal Investigator:

Ross S. Eaton

Business Contact:

Yvonne K. Fuller
Small Business Information at Submission:

Charles River Analytics Inc.
625 Mount Auburn Street Cambridge, MA -

EIN/Tax ID: 042803764
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No