This project supports research in mathematical algorithms and implementations to represent, manipulate, and analyze data, specifically including feature detection, and registration and characterization of natural images. By building on a class of active contour models known as image snakes, the investigators will develop a fast method for object identification, to be used on large volumes of aerial photographs. Combined with higher order nonlinear PDE-based methods for resolving piecewise linear signals, and with shape and size constraints, the final system should be particularly efficient at locking onto predefined shapes. This interdisciplinary work draws on mathematical ideas from fluid dynamics and incorporates datasets from the intelligence community.

This award is supported jointly by the NSF and the Intelligence Community. The Approaches to Combat Terrorism Program in the Directorate for Mathematical and Physical Sciences supports new concepts in basic research and workforce development with the potential to contribute to national security.

Agency
National Science Foundation (NSF)
Institute
Division of Astronomical Sciences (AST)
Type
Standard Grant (Standard)
Application #
0442037
Program Officer
Nigel Sharp
Project Start
Project End
Budget Start
2004-09-01
Budget End
2006-02-28
Support Year
Fiscal Year
2004
Total Cost
$200,000
Indirect Cost
Name
University of California Los Angeles
Department
Type
DUNS #
City
Los Angeles
State
CA
Country
United States
Zip Code
90095