Standalone Multiple Anomaly Recognition Technique (SMART)

Award Information
Agency:
Department of Homeland Security
Branch
n/a
Amount:
$968,958.56
Award Year:
2009
Program:
SBIR
Phase:
Phase II
Contract:
HSHQDC-09-C-00151
Award Id:
n/a
Agency Tracking Number:
DNDO-8.1-08002
Solicitation Year:
2008
Solicitation Topic Code:
08.1-1
Solicitation Number:
n/a
Small Business Information
310 Via Vera Cruz, Suite 107, San Marcos, CA, 92078-2631
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
827430583
Principal Investigator:
Bill Cardoso
bcardoso@creativeelectron.com
Business Contact:
Bill Cardoso
President
bcardoso@creativeelectron.com
Research Institution:
n/a
Abstract
Threat materials can take many shapes and therefore this software tool must be able to perform anomaly detection instead of specific shape detection. The problem of solely relying on a database of images and a matching algorithm is that objects in the image may be shifted, rotated, or the image quality is too poor for a reliable match. Thus, this proposal focuses on the development of an anomaly recognition algorithm that is able to achieve low false positive rates even with low quality input images. Our proposed research will develop an innovative Standalone Multiple Anomaly Recognition Technique (SMART) to determine the presence of contraband in non intrusive inspection (NII) images of trucks and cargo containers. SMART will be able to position in the NII image the location of the potential contraband by using state-of-the-art spectral decomposition analysis techniques to efficiently differentiate the common background of the image against anomalies. These anomalies, in most cases, represent contraband concealed in the cargo.

* information listed above is at the time of submission.

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