Automatic Building Identification under Bomb Damage Conditions

Abstract

Given the vast amount of image intelligence utilized in support of planning and executing military operations, a passive automated image processing capability for target identification is urgently required. Furthermore, transmitting large image streams from remote locations would quickly use available band width (BW) precipitating the need for processing to occur at the sensor location. This paper addresses the problem of automatic target recognition for battle damage assessment (BDA). We utilize an Adaptive Resonance Theory approach to cluster templates of target buildings. The results show that the network successfully classifies targets from non-targets in a virtual test bed environment.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Automatic Target Recognition; Band Width; Battle Damage Assessment; Large Image Streams; Passive Automated Image Processing Capability; Target Identification

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2009 SPIE, All rights reserved.

Publication Date

01 Apr 2009

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