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Using Machine Vision Techniques to Create a Multi-Resolution Obstacle Database

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
74978
Program Year/Program:
2005 / SBIR
Agency Tracking Number:
N043-232-1018
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Cybernet Systems Corporation
3885 Research Park Drive Ann Arbor, MI 48108-2247
View profile »
Woman-Owned: Yes
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2005
Title: Using Machine Vision Techniques to Create a Multi-Resolution Obstacle Database
Agency / Branch: DOD / NAVY
Contract: N00421-05-C-0022
Award Amount: $79,815.00
 

Abstract:

The Navy requires an architecture for acquiring and storing 3-Dimensional obstacle data. An extension of the Terrain Awareness Warning System (eTAWS), the obstacle database must store man-made objects such as buildings, bridges, towers, overpasses, and wires. The system must be able to generate obstacle database data from a number of sources including synthetic aperture radar (SAR), stereo/multiple aerial/satellite photography, and raw geodetic survey data.Cybernet proposes to focus on the collection of 3D obstacle geometry/location based on aerial photography and using advance image processing techniques. This collection process will then be used to populate an indexed database that stores obstacle data at multiple resolutions. By indexing the data, we will be able to reduce the storage requirements by storing redundant data only once. By storing the data at multiple resolutions we allow the application accessing it to balance the tradeoffs corresponding to the different levels of resolution/detail, such as resolution vs. coverage area.

Principal Investigator:

Douglas Haanpaa
Research Engineer
7346682567
dhaanpaa@cybernet.com

Business Contact:

Charles J. Cohen
Vice President, R&D
7346682567
proposals@cybernet.com
Small Business Information at Submission:

CYBERNET SYSTEMS CORP.
727 Airport Boulevard Ann Arbor, MI 48108

EIN/Tax ID: 430924383
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No