Object/Target Discrimination, Recognition, and Identification

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-05-C-0012
Agency Tracking Number: N043-233-0582
Amount: $79,937.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solicitation Year: 2004
Solicitation Topic Code: N04-233
Solicitation Number: 2004.3
Small Business Information
DBA, IAVO Research and Scientific, 1010 Gloria Ave, Durham, NC, 27701
DUNS: 942183781
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 John Merchant
 (781) 444-9426
Business Contact
 John Merchant
Title: President
Phone: (781) 444-9426
Email: merchant.j@comcast.net
Research Institution
Automatic target recognition independent of range and orientation is achieved by using a very different type and much reduced quantity (fewer pixels) of visual information, easily derived from the output of any standard image sensor by variance sub-sampling. The very low pixel density of the resulting variance image directly provides (1) high pose-immunity in any one target-reference match, and (2) enables multiple (variance) references to be stored of each target type to provide coverage over the full set of required poses. In spite of its low pixel density, variance sampling provides high resolution information essential for recognition. Conventional Nyquist sampling, on the other hand, requires high pixel density to provide the essential high resolution information and is thereby highly pose-sensitive and also highly processing and memory intensive. This very different (variance) and much reduced quantity of visual information is used almost exclusively by human vision to perform recognition. Its transition to ATR systems, that seek to emulate human vision, will result in a major advance in ATR capability.

* Information listed above is at the time of submission. *

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