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A Hybrid Approach to Disturbed Soil and Mine Detection

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
59761
Program Year/Program:
2002 / SBIR
Agency Tracking Number:
N022-0187
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Intelligent Automation, Inc.
15400 Calhoun Drive Suite 400 Rockville, MD 20855-
View profile »
Woman-Owned: Yes
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2002
Title: A Hybrid Approach to Disturbed Soil and Mine Detection
Agency / Branch: DOD / NAVY
Contract: N68335-03-C-0034
Award Amount: $69,991.00
 

Abstract:

"IAI and Prof. Chang of the University of Maryland at Baltimore County (UMBC), jointly propose a new hybrid framework for disturbed soil and mine detection using airborne images from two perspectives: spatial and spectral. The first approach is a spatialapproach, which mainly focuses on texture analysis. The idea is motivated by the fact that, the ground texture will be disturbed if mines are planted. By systematically looking the gray level changes in an airborne image, one can obtain texture patternsthat are unusual. This approach is applicable to EO, IR, hyperspectral, and SAR images. The second approach is a spectral approach and has two steps. First, a new automatic target generation process (ATGP) is used to generate a set of potential targets(mines) from the image data in an unsupervised fashion without using any prior knowledge. The ATGP idea originates from the concept of orthogonal subspace projection (OSP) in signal processing. Second, a novel Automatic Target Detection and ClassificationAlgorithm (ATDCA) is used to identify the potential mines. The algorithm can be used to detect anomalies (new and unknown mines) in blind environments. The algorithm is suitable for surveillance operations where the objective is to detect the presence ofany potential mines. The proposed algorithm will be useful for surveillance. The market for military applications is quite large. The Commercial marketplace for this algorithm may be equally

Principal Investigator:

Chiman Kwan
Director of Research & De
3012945200
ckwan@i-a-i.com

Business Contact:

Marc B. Toplin
Director of Contracts
3012945200
mtoplin@i-a-i.com
Small Business Information at Submission:

Intelligent Automation, Inc.
7519 Standish Place, Suite 200 Rockville, MD 20855

EIN/Tax ID: 521497192
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No