Using hardware-assisted geometric hashing for high-speed target acquisition and guidance (original) (raw)
1997, Spie Proceedings Series
Geometric hashing provides a reliable and transformation independent representation of a target. The characterization of a target object is obtained by establishing a vector basis relative to a number of interest points unique to the target. The number of basis points required is a function of the dimensionality of the environment in which the technique is being used. This basis is used to encode the other points in the object constructing a highly general (transformation independent) representation of the target. The representation is invariant under both affine and geometric transformations of the target interest points. Once a representation of the target has been constructed a simple voting algorithm can be used to examine sets of interest points extracted from subsequent image in order to determine the possible presence and location of that target. Once an instance of the object has been located further computation can be undertaken to determine its scale, orientation, and deformation due to changes in the parameters related to the viewpoint. This information can be further analyzed to provide guidance. This paper discusses the complexity measures associated with task division and target image processing using geometric hashing. These measures are used to determine the areas which will most benefit from hardware assistance, and possible parallelism. These issues are discussed in the context of an architecture design, and a high speed (hardware assisted) geometric hashing approach to target recognition is proposed.
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