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
Agency Tracking Number:
N092-094-0399
Solicitation Year:
2009
Solicitation Topic Code:
N092-094
Solicitation Number:
2009.2
Small Business Information
Technology Service Corporation
1900 S. Sepulveda Blvd, Suite 300, Los Angeles, CA, 90025
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
053885604
Principal Investigator
 Uri Bernstein
 Corporate Senior Staff
 (310) 954-2200
 uri.bernstein@tsc.com
Business Contact
 Lee Moyer
Title: Vice President
Phone: (703) 995-9553
Email: lee.moyer@tsc.com
Research Institution
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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