Real-time identification of fixed targets

Patricia J. Rowland; Kevin A. Kreeger; Albert R. Sanders

doi:10.1117/12.58050

1 April 1992 Real-time identification of fixed targets

Patricia J. Rowland, Kevin A. Kreeger, Albert R. Sanders

Author Affiliations +

Proceedings Volume 1623, The 20th AIPR Workshop: Computer Vision Applications: Meeting the Challenges; (1992) https://doi.org/10.1117/12.58050
Event: The 20th AIPR Workshop, 1991, McLean, VA, United States

Abstract

Fixed targets such as bridges, airfields, and buildings are of military significance and their value is constantly being appraised as the battle scenario evolves. For examples, a building thought to be of no significance may be reappraised, through intelligence reports, as a military command center. The ability to quickly strike these targets with a minimal amount of a priori information is necessary. The requirements placed on such a system are: (1) Rapid turnaround time from the moment the decision is made to attack. Depending on the user organization, this time ranges from fifteen minutes to twelve hours. (2) Minimal a priori target information. There is likely to be no imagery data base of the target, and the system may be required to operate with as little information as an overhead photograph. (3) Real time recognition of the target. Terminal guidance of the weapons delivery system to a specified destructive aimpoint of will be impacted by the recognition system. (4) Flexibility to attack a variety of targets. A data base of known high value fixed targets (HVFT) may be stored, but the sudden inclusion of new targets must be accommodated. This paper will discuss a real time implementation of a model based approach to automatically recognize high value fixed targets in forward looking infrared (FLIR) imagery. This approach generates a predictive model of the expected target features to be found in the image, extracts those feature types from the image, and matches the predictive model with the image features. A generic approach to the description of the target features has been taken to allow for rapid preparation of the models from minimal a priori target information. The real time aspect has been achieved by implementing the system on a massively parallel single instruction, multiple data architecture. An overview of an entire system approach to attack high value fixed targets will be discussed. The automatic target recognizer (ATR), which is a part of this system, will be discussed in detail and results of the ATR operating against HVFT in FLIR imagery will be shown.

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Patricia J. Rowland, Kevin A. Kreeger, and Albert R. Sanders "Real-time identification of fixed targets", Proc. SPIE 1623, The 20th AIPR Workshop: Computer Vision Applications: Meeting the Challenges, (1 April 1992); https://doi.org/10.1117/12.58050

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