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Proceedings Paper

Model-based system for vehicle detection and identification
Author(s): Jerald A. Herstein; Rodney L. Pickens; William W. Boyd
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Paper Abstract

The detection and identification of vehicles in forward looking infrared (FLIR) images presents a number of problems. Not only is the view of the vehicle influenced by its orientation and the position of the sensor, but it is also affected by the environment. To counter these effects, we have developed a set of algorithms which use models of both the vehicles of interest and the environment to aid detection and identification. This algorithm set consists of an area-of-interest locator, an object segmenter, and a template matcher. These algorithms are controlled by a process which uses information about the vehicles and the environment to select input parameters for the processing algorithms. This article contains a description of the detection and identification system algorithms, the performance characterization of the individual algorithms, and the temporal fusion performance prediction results.

Paper Details

Date Published: 20 October 1993
PDF: 22 pages
Proc. SPIE 1957, Architecture, Hardware, and Forward-Looking Infrared Issues in Automatic Target Recognition, (20 October 1993); doi: 10.1117/12.161431
Show Author Affiliations
Jerald A. Herstein, Texas Instruments Inc. (United States)
Rodney L. Pickens, Texas Instruments Inc. (United States)
William W. Boyd, Texas Instruments Inc. (United States)

Published in SPIE Proceedings Vol. 1957:
Architecture, Hardware, and Forward-Looking Infrared Issues in Automatic Target Recognition
Lynn E. Garn; Lynda Ledford Graceffo, Editor(s)

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