An Automated Fish Migration Pattern Monitoring System Using Shape Descriptors for Pattern Recognition

Award Information
Agency: Department of Agriculture
Branch: N/A
Contract: 2003-33610-13132
Agency Tracking Number: 2003-00630
Amount: $75,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2003
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
3320 Mill Spring Drive, Fairfax, VA, 22031
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Robert Schoenberger
 (703) 273-3202
 rob@machinevision1.com
Business Contact
 Robert Schoenberger
Title: President
Phone: (703) 273-3202
Email: rob@machinevision1.com
Research Institution
N/A
Abstract
NON-TECHNICAL SUMMARY: Fish ecology and environmental research scientists have an urgent need for an automated fish recognition system for monitoring fish migration patterns. Many fish species are known to travel for great distances during their life cycle. As they travel past dams equipped with a fish passage, their species, size, total number, and the time are recorded for migration pattern studies. These are very important data for biologists, especially for the research of endangered species and effects of environmental change. This data collection process is currently performed manually at these dam passageways. Manual monitoring and recognition of fish 24 hours a day or reviewing hours of recorded video taps during the entire migration season is a very tedious task and, most of the time, results in unreliable data. Additionally, report generation and access to data are inconvenient. The result of this proposed research project will have great impacts on fish behavior and migration pattern studies, especially for endangered species, as well as the studies of the environmental effects due to man-made changes. Compared to the current process, a fully automated fish recognition system will provide more reliable data with greatly reduced efforts for researchers. This research will lead to an affordable vision system for environmental studies and commercial fishery.

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

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