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Florida Institute of Technology

1992

Articles 1 - 8 of 8

Full-Text Articles in Engineering

Bayesian Defeat Of Camouflage, Rufus H. Cofer Sep 1992

Bayesian Defeat Of Camouflage, Rufus H. Cofer

Electrical Engineering and Computer Science Faculty Publications

A new technique is shown for refining and reducing incoming camouflage data based upon the Bayesian paradigm. Innovation is displayed in use of a statistical conditioning sequence that avoids the need to form target features from the data. The result is a simplified and more accurate probabilistic indication of actual target presence. This probabilistic indication can then be incorporated into a variety of target detection scenarios or, alternately, to form the basis of a theoretically optimal Bayesian target detector. Numeric simulation is presented to show the effectiveness of the technique against simulated camouflage

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Supercomputer-Based Spherical Scene Projector, Harold K. Brown, John G. Madry, Rufus H. Cofer, Samuel Peter Kozaitis Sep 1992

Supercomputer-Based Spherical Scene Projector, Harold K. Brown, John G. Madry, Rufus H. Cofer, Samuel Peter Kozaitis

Electrical Engineering and Computer Science Faculty Publications

A multi-technology high performance computing system based on the Open Parallel Architecture Design Specification (OPADS) platform is being evaluated for use as a graphics engine for spherical scene projection. This system is designed to make available the massive quantities of real-time processing power needed to support complete real time scene generation and projection of complex dynamical maneuvers for applications such as scientific visualization and three dimensional database creation and interaction. A comparison is also provided between head mounted projection systems and walk-in spherical scene projection systems.

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Explanation Mode For Bayesian Automatic Object Recognition, Thomas L. Hazlett, Rufus H. Cofer, Harold K. Brown Sep 1992

Explanation Mode For Bayesian Automatic Object Recognition, Thomas L. Hazlett, Rufus H. Cofer, Harold K. Brown

Electrical Engineering and Computer Science Faculty Publications

One of the more useful techniques to emerge from AI is the provision of an explanation modality used by the researcher to understand and subsequently tune the reasoning of an expert system. Such a capability, missing in the arena of statistical object recognition, is not that difficult to provide. Long standing results show that the paradigm of Bayesian object recognition is truly optimal in a minimum probability of error sense. To a large degree, the Bayesian paradigm achieves optimality through adroit fusion of a wide range of lower informational data sources to give a higher quality decision - a very …

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Practical Constraints Pertinent To The Design Of Neural Networks, Said Sadek Abdallah, Rufus H. Cofer Aug 1992

Practical Constraints Pertinent To The Design Of Neural Networks, Said Sadek Abdallah, Rufus H. Cofer

Electrical Engineering and Computer Science Faculty Publications

in designing a feedforward neural network for numerical computation using the backpropagation algorithm it is essential to know that the resulting network has a practical global minimum, meaning that convergence to a stationary solution can be achieved in reasonable time and using a network of reasonable size. This is in contrast to theoretical results indicating that any square-integrable (L2) function can be computed assuming that an unlimited number of neurons are available. A class of problems is discussed that does not fit into this category. Although these problems are conceptually simple, it is shown that in practice convergence to a …

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Feature-Based Correlation Filters For Distortion Invariance, Samuel Peter Kozaitis, Robert Petrilak, Wesley E. Foor Jul 1992

Feature-Based Correlation Filters For Distortion Invariance, Samuel Peter Kozaitis, Robert Petrilak, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

In an optical correlator, binary phase-only filters (BPOFs) that recognize objects that vary in a nonrepeatable way are essential for recognizing objects from actual sensors. An approach is required that is as descriptive as a BPOF yet robust to object and background variations of an unknown or nonrepeatable type. We developed a BPOF that was more robust than a synthetic discriminant function (SDF) filter. This was done by creating a filter that retained the invariant features of a training set. By simulation, our feature-based filter offered a range of performance by setting a parameter to different values. As the value …

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Optical Estimation Of Fractal Dimension For Image Assessment, Samuel Peter Kozaitis, Rufus H. Cofer Jul 1992

Optical Estimation Of Fractal Dimension For Image Assessment, Samuel Peter Kozaitis, Rufus H. Cofer

Electrical Engineering and Computer Science Faculty Publications

We modeled an optical system for estimation of the fractal dimension to provide a measure of surface roughness for an entire image and for image segmentation. Although the simulated optical result was similar to that calculated by digital techniques, both suffered from problems known to occur with estimating fractal dimension. Furthermore, the optical estimation did not have as good a resolution as that obtained with digital estimates due primarily to the limited dynamic range of the detector.

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Multiresolution Template Matching Using An Optical Correlator, Samuel Peter Kozaitis, Zia Saquib, Rufus H. Cofer, Wesley E. Foor Jul 1992

Multiresolution Template Matching Using An Optical Correlator, Samuel Peter Kozaitis, Zia Saquib, Rufus H. Cofer, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

Infrared imagery of 512 × 512 pixels was processed with 128 × 128 arrays by computer simulation of an optical correlator using various correlation filters. Pyramidal processing using binary phase-only filters (BPOFs), synthetic discriminant function (SDF) filters, and feature-based filters was used to process an entire image in parallel at different resolutions. Results showed that both SDF and feature-based filters were more robust to the effects of thresholding input imagery than BPOFs. The feature-based filters offered a range of performance by setting a parameter to different values. As the value of the parameter was changed, correlation peaks within the training …

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Detection, Location, And Quantification Of Structural Damage By Neural-Netprocessed Moire Profilometry, Barry G. Grossman, Frank S. Gonzalez, Joel H. Blatt, Jeffery A. Hooker Mar 1992

Detection, Location, And Quantification Of Structural Damage By Neural-Netprocessed Moire Profilometry, Barry G. Grossman, Frank S. Gonzalez, Joel H. Blatt, Jeffery A. Hooker

Electrical Engineering and Computer Science Faculty Publications

The development of efficient high speed techniques to recognize, locate, and quantify damage is vitally important for successful automated inspection systems such as ones used for the inspection of undersea pipelines. Two critical problems must be solved to achieve these goals: the reduction of nonuseful information present in the video image and automatic recognition and quantification of extent and location of damage. Artificial neural network processed moire profilometry appears to be a promising technique to accomplish this. Real time video moire techniques have been developed which clearly distinguish damaged and undamaged areas on structures, thus reducing the amount of extraneous …

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