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Automated Feature Extraction Capabilities for the Development of High-Resolution GEOINT Feature Data and Constructing Correlated Databases

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: H92222-07-p-0007
Agency Tracking Number: S062-012-0102
Amount: $99,980.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SOCOM06-012
Solicitation Number: 2006.2
Timeline
Solicitation Year: 2006
Award Year: 2006
Award Start Date (Proposal Award Date): 2006-11-27
Award End Date (Contract End Date): 2007-05-27
Small Business Information
1900 S. Sepulveda Blvd, Suite 300
Los Angeles, CA 90025
United States
DUNS: N/A
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Uri Bernstein
 Corporate Senior Staff
 (310) 954-2200
 ubernstein@tsc.com
Business Contact
 Michael Syracuse
Title: Vice President
Phone: (301) 565-2970
Email: msyracuse@tsc.com
Research Institution
N/A
Abstract

Data resources available for automatic feature extraction (AFE) have expanded significantly in the last few years. Available sensor data now includes high-resolution multispectral and hyperspectral sensors, synthetic aperture radar (SAR), and accurate height measurement sensors such as LIDAR and interferometric SAR (IFSAR). Current AFE tools are unable to fuse and process all the new types of sensor data. TSC proposes a program for AFE algorithm development and testing that ingests all available sensor data, and extracts buildings, structures, road networks, and waterways. The method uses a knowledge-based expert system (KBES) that is trained with initial user interaction. The KBES methodology facilitates the fusion of multiple sensors, and also adapts easily to different combinations of sensors. TSC will develop algorithms for extracting vector features from the input raster data, and creating an output in a vector map format

* Information listed above is at the time of submission. *

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