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NEURAL NET BASED PRIMING AND MODEL BASED ATR USING MOTION CUES

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
18427
Program Year/Program:
1994 / SBIR
Agency Tracking Number:
18427
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
LNK CORP., INC.
6811 Kenilworth Avenue, Suite 306 Riverdale, MD 20737
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Woman-Owned: No
Minority-Owned: Yes
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 1994
Title: NEURAL NET BASED PRIMING AND MODEL BASED ATR USING MOTION CUES
Agency / Branch: DOD / USAF
Contract: N/A
Award Amount: $298,122.00
 

Abstract:

Object-oriented methodologies such as model-based vision provide a robust and more intelligent solution to the ATR problem. Because these methodologies exploit a priori knowledge of a limited number of target models, while allowing the targets to be oriented towards the viewer in any arbitrary fashion, they result in a powerful ATR system. The central focus of this proposal is on building an automatic target recognition system for identifying mobile targets using an object-image alignment approach. Using this approach, we propose to develop a two stage recognition algorithm. The first stage of this algorithm makes use of the three-point object-image correspondence theorim of Huttenlocher and Ullman (1990) to narrow the search for constrained matching of object-image pairs. The second stage of the algorithm uses the mean-field annealing techique to compute the object-image transformation parameters from multiple matches by minimizing a least-squares measure. For segmentation of the target from its background, we employ a motion-based segmentation algorithm developed earlier by LNK.

Principal Investigator:

Dr Srinevasan Raghaven
3019273223

Business Contact:

Small Business Information at Submission:

Lnk Corp., Inc.
6811 Kneilworth Avenue, Suite 306 Riverdale, MD 20737

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