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24 May 1996 Three-dimensional moment invariants for automated target recognition
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Invariant target representation is desirable in any target recognition system. The representation that captures the salient attributes of a target independent of the viewing geometry will reduce the target search space in the recognition system. Three dimensional moment invariants are specially useful due to the increased interest in the ATR community on synthetic aperture radar and laser radar that generates 3D snapshot of the real world as well as passive sensors that produce sequential imagery that represents a 3D view of the sensed scene due to the relative motion of the target and sensor. The distributed (imaging) sensor processing part of the increasingly popular distributed surveillance systems also generate or could generate 3D information about the targets and their background scene. In this paper, the application of 3D moment invariants and perspective invariants for modeling automated target recognition is reviewed. Both two and three dimensional algebraic and moment invariants as well as perspective invariants have been derived and used for various type of recognition. Problems with numerical computation and partially occluded objects have been encountered and resolved. The theory has been demonstrated for synthetic target recognition and the method appears promising for implementation on real imagery.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tayib I. Samu, Firooz A. Sadjadi, and Ernest L. Hall "Three-dimensional moment invariants for automated target recognition", Proc. SPIE 2756, Automatic Object Recognition VI, (24 May 1996);

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