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When data sets are analyzed, statistical pattern recognition is often used to find the information hidden in the data. Another approach to information discovery is data mining. Data mining is concerned with finding previously undiscovered relationships in data sets. Rough set theory provides a theoretical basis from which to find these undiscovered(More)
The techniques of Lie group analysis can be used to determine absolute invariant functions which serve as classiier functions in object recognition problems. Previously, the Lie groups were found for the conservation equation describing the energy exchange at the surface of an object viewed with an infrared camera. The result was that only trivial absolute(More)
| Object recognition requires robust and stable features that are unique in feature space. Lie group analysis provides a constructive procedure to determine such features, called invariants, when they exist. Absolute in-variants are rare in general, so quasi-invariants relax the restrictions required for absolute invariants and, potentially, can be just as(More)
Recent research in the calculation and exploitation of object/image relations suggests new approaches to ATR. The resulting conceptual advances transform the ATR problem into a feature extraction and correspondence problem. This paper addresses several application areas and demonstrates how the corresponding research areas are related by a common theory.
A formulation of signal-to-noise ratio is constructed that uses temporal integrated images from image sequences. Given a blurred image that drifts horizontally at various speeds and at various linear blurs, we prove that this formulation of the signal-to-noise ratio consistently increases with an increase in speed. This increase is shown to model the trends(More)