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Proceedings Paper

Integrated oceanographic image understanding system
Author(s): Matthew Lybanon; Sarah H. Peckinpaugh; Ronald J. Holyer; Vivian Cambridge
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Paper Abstract

A system was assembled to study several aspects of locating ship targets from infrared imagery. The system was either placed on shore sites or installed on an aircraft to collect data on the scene. The primary sensor was an infrared camera which produced images of the scene at standard RS-l70 rates. Requirements that included real time operation dictated the use of a parallel architecture for this task. As no suitable commercial systems were avail able, a custom array of bit slice microprocessors was assembled for the task. Through extensive field tests strengths and limitations of the design have been identified. These lessons are being applied to the development of next generation systems. A gimbal mounted infrared camera with digitization circuitry presents a new 256 by 256 pixel image to the parallel pipelined array of 17 bit slice microprocessors thirty times a second. To extend processor performance beyond the standard commercial microprocessors. two basic bit slice designs were employed. The bit slice machines were highly tuned for the assigned tasks and algorithms. Unfortunately this restricted the desired flexibility to readily examine alternate algorithms. The fundamental architecture concept performed well quickly reducing the large array of data to manageable set of information. Real time operator displays were driven to monitor the progress of each test run. Results of the system operation were stored on video and digi tal recorders permitting more detailed analysis after each test. Non real time data reduction provided many insights into the system operation and to algorithm improvements. Substantial operator interaction. and data interpretation was required greatly slowing the post test analysis phase. Overwhelmed with data, the analysts focused on locating a few data segments of interest. Significant work remains in improving the interfaces between the field data and the powerful laboratory computers. Automation of the data analysis is also needed to efficiently evaluate the great volume of field information. Continuing improvements in Artificial Intelligence, Expert Systems, Neural Networks, and other areas may help here.

Paper Details

Date Published: 1 April 1991
PDF: 10 pages
Proc. SPIE 1406, Image Understanding in the '90s: Building Systems that Work, (1 April 1991); doi: 10.1117/12.47983
Show Author Affiliations
Matthew Lybanon, Naval Oceanographic and Atmospheric Research Lab. (United States)
Sarah H. Peckinpaugh, Naval Oceanographic and Atmospheric Research Lab. (United States)
Ronald J. Holyer, Naval Oceanographic and Atmospheric Research Lab. (United States)
Vivian Cambridge, Sverdrup Technology, Inc. (United States)


Published in SPIE Proceedings Vol. 1406:
Image Understanding in the '90s: Building Systems that Work

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