• Publications
  • Influence
Multivariant technique for multiclass pattern recognition.
A technique for multiclass optical pattern recognition of different perspective views of an object is described and a single averaged matched spatial filter is produced from a weighted linear combination of these functions. Expand
Minimum average correlation energy filters.
The synthesis of a new category of spatial filters that produces sharp output correlation peaks with controlled peak values is considered, and these filters are referred to as minimum average correlation energy filters. Expand
Minimum noise and correlation energy optical correlation filter.
This new minimum noise and correlation energy filter approach introduces the concept of using the spectral envelope of the training images and the noise power spectrum to obtain a tight bound to the energy minimization problem that is associated with distortion-invariant filters in noise. Expand
Unified synthetic discriminant function computational formulation.
  • D. Casasent
  • Computer Science, Medicine
  • Applied optics
  • 15 May 1984
A general basis function and hyperspace description of SDFs is provided, a derivation showing the generality of the correlation matrix observation space is advanced, and a unified SDF filter synthesis technique is detail for five different types of pattern recognition problem. Expand
Position, rotation, and scale invariant optical correlation.
A new optical transformation that combines geometrical coordinate transformations with the conventional optical Fourier transform is described, which is invariant to both scale and rotational changes in the input object or function. Expand
An improvement on floating search algorithms for feature subset selection
The proposed algorithm improves the state-of-the-art sequential forward floating selection algorithm by adding an additional search step called ''replacing the weak feature'' to check whether removing any feature in the currently selected feature subset and adding a new one at each sequential step can improve the current feature subset. Expand
Correlation synthetic discriminant functions.
These correlation synthetic discriminant functions (SDFs) are extensions of earlier projection SDFs and provide control of the sidelobe levels and the shape of the output correlation function as well as its peak intensity. Expand
Detection filters and algorithm fusion for ATR
New detection algorithms and the fusion of their outputs are considered to reduce the probability of false alarm P(FA) while maintaining high probability of detection P(D) in infrared imagery. Expand
Classifier and shift-invariant automatic target recognition neural networks
A new feature space trajectory classifier neural network is described that identifies the class and pose of each object, rejects clutter false alarms, and overcomes various issues associated with other classier neural networks. Expand
Gaussian-minimum average correlation energy filters.
It is shown that the MACE filter cannot always recognize intermediate images of true class objects (e.g., aspect views or rotations midway between two training images). Expand