Material Classification for Physics-Based Sensor Simulation Using Stereo-Pair Imagery

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$79,818.00
Award Year:
2009
Program:
SBIR
Phase:
Phase I
Contract:
N68335-09-C-0456
Award Id:
92607
Agency Tracking Number:
N092-094-0399
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1900 S. Sepulveda Blvd, Suite 300, Los Angeles, CA, 90025
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
053885604
Principal Investigator:
UriBernstein
Corporate Senior Staff
(310) 954-2200
uri.bernstein@tsc.com
Business Contact:
LeeMoyer
Vice President
(703) 995-9553
lee.moyer@tsc.com
Research Institute:
n/a
Abstract
Current simulators can display very detailed imagery over very large geographic training areas in both visual and sensor channels. To provide a high-fidelity sensor channel, the simulation must be physics-based, and must rely on knowledge of the material properties of the simulation area. The proposed work includes the development and evaluation of algorithms for an advanced classifier and feature extractor that uses both color/multispectral imagery and digital elevation maps. It is specifically targeted to exploit the stereo imagery from the latest generation of earth imaging satellites. The extractor uses an initial multi-scale object-based process to segment the image, followed by an expert system for object classification and feature extraction. The proposed option tasks include the exploitation of height and intensity texture, and the extraction and representation of spatial variability within a material class.

* information listed above is at the time of submission.

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