Imagery Exploitation Applications of Neuroscience

Award Information
Agency: Department of Defense
Branch: National Geospatial-Intelligence Agency
Contract: NMA401-02-C-0006
Agency Tracking Number: M021-0007
Amount: $99,932.00
Phase: Phase I
Program: SBIR
Awards Year: 2002
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
Chi Systems, Inc.
Gwynedd Office Park, 716 N. Bethlehem Pike, Ste 300, Lower Gwynedd, PA, 19002
DUNS: 161162995
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 James Eilbert
 Project Manager
 (215) 542-1400
 jeilbert@chiinc.com
Business Contact
 Phil Rollhauser
Title: Mgr, Contracts
Phone: (215) 542-1400
Email: prollhauser@chiinc.com
Research Institution
N/A
Abstract
"The primary objective of this effort is to develop a robust object matching system that can be applied to a variety of image exploitation needs. The analytical decisions by our proposed context aware, neural column-based image expert (CANCIE) will utilizecontext knowledge or expectations about the current "mental space," as well as imagery having an object matching component and an analysis component. CANCIE will extract and compare information about objects or a group of objects in imagery usinginnovative neuromorphic techniques. In particular, it will emulate the static organization of initial visual field response within cortical columns, as well as the evolution of the response pattern as it is modified by feedback interactions. The principlesencoded in the columnar organization that will be utilized in CANCIE include retinotopic organization, the multiplexing of information in individual neurons, and the trend toward larger visual fields with various types of spatial invariance farther alongthe visual pathway. CANCIE will support both a change detection mode and a context-sensitive, object-matching mode. An interface will be provided that will allow an image analyst to specify a set of context parameters that will impacts it processing. Theneed for systems that can reduce the workload of image and geospatial analysts is growing, and presents a variety of market opportunities. While the approach we propose is general, a CAN

* information listed above is at the time of submission.

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