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Florida Institute of Technology

Electrical Engineering and Computer Science Faculty Publications

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Full-Text Articles in Engineering

Fiber Optic Sensor For The Simultaneous Detection Of Strain And Temperature, Barry G. Grossman, Walid Emil Costandi Mar 1993

Fiber Optic Sensor For The Simultaneous Detection Of Strain And Temperature, Barry G. Grossman, Walid Emil Costandi

Electrical Engineering and Computer Science Faculty Publications

For simple interferometric fiberoptic sensors, the effects of strain and temperature are indistinguishable. This paper addresses that problem by demonstrating a single wavelength, two-mode polarimetric fiberoptic sensor capable of simultaneously measuring temperature and strain. The sensor consists of two interferometers, a polarimetric and a two-mode, formed in a single elliptical core fiber. The interferometers respond with different sensitivities to strain and temperature like simultaneous functions of the two variables. A technique is developed by which the outputs of the interferometers are used simultaneously to measure strain and temperature with rms errors less than 30 με and 1°C. Finally, measurement results …

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Optical Image Analysis Using Fractal Techniques, Samuel Peter Kozaitis, Harold Gregory Andrews, Wesley E. Foor Feb 1993

Optical Image Analysis Using Fractal Techniques, Samuel Peter Kozaitis, Harold Gregory Andrews, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

Using an optical technique, we classified images of natural terrain based on their fractal dimension. We calculated the fractal dimension from an optically generated power spectrum obtained with a magneto-optic spatial light modulator (SLM). By using the fractal dimension to classify images of natural terrain, our post processing was simpler that when a ring-wedge detector was used.

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Feature-Based Correlation Filters For Object Recognition, Samuel Peter Kozaitis, Wesley E. Foor Feb 1993

Feature-Based Correlation Filters For Object Recognition, Samuel Peter Kozaitis, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

Using an optical correlator, we experimentally evaluated a binary phase-only filter (BPOF) designed to recognize objects not in the training set used to design the filter. Such a filter is essential for recognizing objects from actual sensors. We used an approach that is as descriptive as a BPOF yet robust to object and background variations of an unknown or nonrepeatable type. We generated our filter by comparing the values of spatial frequencies of a training set. Our filter was easily calculated and offered potentially superior performance to other correlation filters.

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Design Of Distortion-Invariant Correlation Filters Using Supervised Learning, Samuel Peter Kozaitis, Rufus H. Cofer, Wesley E. Foor Jan 1993

Design Of Distortion-Invariant Correlation Filters Using Supervised Learning, Samuel Peter Kozaitis, Rufus H. Cofer, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

We designed binary phase-only filters from a training set of images using a statistical approach. We forced images into clusters and designed filters to recognize objects from that cluster. We report on results obtained by computer simulation comparing the performance of filters to recognize objects from clusters of one and two classes.

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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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Neural Control Of Smart Electromagnetic Structures, Michael Thursby, Kisuck Yoo, Barry G. Grossman Dec 1991

Neural Control Of Smart Electromagnetic Structures, Michael Thursby, Kisuck Yoo, Barry G. Grossman

Electrical Engineering and Computer Science Faculty Publications

Artificial neural networks (ANNs) and their ability to model and control dynamical systems for smart structures, including sensors, actuators, and plants, are directly applicable to the smart electromagnetic structures (SEMS) concept. The application of neural networks to the area of controls is being reported frequently. The ability of a structure to adapt to impinging electromagnetic (EM) energy will allow the structure to change its reflection characteristics and thus to change its radar signature. By embedding a control element in the structure of a single microstrip patch element, its electrical characteristics can be changed. If such an element can be controlled …

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Composite Damage Assessment Employing An Optical Neural Network Processor And An Embedded Fiberoptic Sensor Array, Barry G. Grossman, Xing Gao, Michael H. Thursby Dec 1991

Composite Damage Assessment Employing An Optical Neural Network Processor And An Embedded Fiberoptic Sensor Array, Barry G. Grossman, Xing Gao, Michael H. Thursby

Electrical Engineering and Computer Science Faculty Publications

This paper discusses a novel approach for composite damage assessment with potential for DoD, NASA, and commercial applications. We have analyzed and modeled a two dimensional composite damage assessment system for real-time monitoring and determination of damage location in a composite structure. The system combines two techniques: a fiberoptic strain sensor array and an optical neural network processor. A two dimensional fiberoptic sensor array embedded in the composite structure during the manufacturing process can be used to detect changes in the mechanical strain distribution caused by subsequent damage to the structure. The optical processor, a pre-trained Kohonen neural network, has …

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Experimental Performance Of A Binary Phase-Only Optical Correlator Using Visual And Infrared Imagery, Samuel Peter Kozaitis, Sandra L. Halby, Wesley E. Foor Sep 1990

Experimental Performance Of A Binary Phase-Only Optical Correlator Using Visual And Infrared Imagery, Samuel Peter Kozaitis, Sandra L. Halby, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

Experimental results of an optical binary phase-only correlator using both visual and IR imagery are presented. The inputs to the correlator originate from actual aerial imagery containing aircraft and a variety of distortions. Filters used as a database for the system are derived from models of aircraft. Digital image processing techniques are used on images before being input into the optical correlator to enhance the performance of the system. Both noise removing and segmentation techniques are investigated. Input images to the correlator are displayed on a 128×128 magneto-optic spatial light modulator (SLM). Experimental results are presented which show that the …

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Optical Processors For Smart Structures, Barry G. Grossman, Howard Hou, Ramzi H. Nassar Sep 1990

Optical Processors For Smart Structures, Barry G. Grossman, Howard Hou, Ramzi H. Nassar

Electrical Engineering and Computer Science Faculty Publications

For underwater fiber-optic sensor arrays containing hundreds of sensors as well as smart aerospace structures and skins using fiber-optic strain sensor arrays, the output of the sensors are optical signals that are a function of the measurand. We are also employing optical signals to energize smart-structure actuators (shape-memory alloys). An all-optical processor would thus seem to be logical choice for the processor since we must simultaneously process, in real time, multiple optical input (sensor) signals and generate multiple output (actuator) signals. In addition, with an all-optical processor, there would be no reduction in processor performance due to converting between optical …

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Processing Of One-Fiber Interferometric Fiber-Optic Sensor Signals, A. Tino Alavie, Barry Grossman, Michael Thursby Feb 1990

Processing Of One-Fiber Interferometric Fiber-Optic Sensor Signals, A. Tino Alavie, Barry Grossman, Michael Thursby

Electrical Engineering and Computer Science Faculty Publications

Recent research conducted in the Fiber -Optic Sensor Systems Laboratory at Florida Institute of Technology in fiber -optic strain sensors for use in smart structures has concentrated primarily on one -fiber interferometers. Sensors using this technique are of particular interest because they are rugged and provide reasonable strain sensitivities, typically a thousand times that of microbend sensors, while requiring only a single optical fiber. As in two -fiber interferometers, some method must be used to convert the sensor signal output to an absolute strain value. One technique is to provide active phase tracking to keep the sensor signal output at …

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Fiber-Optic Sensor And Smart Structures Research At Florida Institute Of Technology, Barry Grossman, Tino Alavie, Fred Ham, Jorge Franke, Michael Thursby Feb 1990

Fiber-Optic Sensor And Smart Structures Research At Florida Institute Of Technology, Barry Grossman, Tino Alavie, Fred Ham, Jorge Franke, Michael Thursby

Electrical Engineering and Computer Science Faculty Publications

This paper discusses the fundamental issues being investigated by Florida Institute of Technology (F.I.T.) to implement the technology of smart structural systems for DoD, NASA, and commercial applications. Embedded sensors and actuators controlled by processors can provide a modification of the mechanical characteristics of composite structures to produce smart structures1-3. Recent advances in material science have spurred the development and use of composite materials in a wide range of applications from rotocraft blades and advanced tactical fighter aircraft to undersea and aerospace structures. Along with the advantages of an increased strength-to-weight ratio, the use of these materials has raised a …

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Image Preprocessing For Phase- Only Filtering, Samuel Peter Kozaitis, Atikom Roeksabutr Jan 1990

Image Preprocessing For Phase- Only Filtering, Samuel Peter Kozaitis, Atikom Roeksabutr

Electrical Engineering and Computer Science Faculty Publications

We compare the performance of an optical binary phase-only correlator using several nonlinear filters for preprocessing. An image of an airfield with different but similar appearing planes is used as the input data. The performance of the correlator was measured by examining several parameters in the correlation plane. Performance criteria are the signal-to-clutter ratio, the signal-to-noise ratio for objects within the same class, and the variance of the correlation peak within a class. Input images to the correlator were preprocessed using nonlinear filters based on both median filtering and adaptive filtering. The preprocessing improved the performance of the correlator by …

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Ground Exploitation Using A Binary Phase-Only Optical Correlator, Samuel Peter Kozaitis, Sandra L. Halby, Wesley E. Foor Jan 1990

Ground Exploitation Using A Binary Phase-Only Optical Correlator, Samuel Peter Kozaitis, Sandra L. Halby, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

Experimental results of an optical binary phase-only correlator using aerial imagery for ground exploitation is presented. The correlator uses magnetooptic spatial light modulators (SLMs) for dynamic operation. Input images to the correlator originate from actual aerial imagery containing aircraft and a variety of distortions. Digital image processing techniques are used on images before being input into the optical correlator to enhance the performance of the system. Filters or templates used as a database for the system are derived from models of aircraft. Rotation and scale invariance is achieved through an adaptive filtering technique in which filters are displayed sequentially against …

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Digital Optical Iterative Pattern Recognizer, Samuel Peter Kozaitis, C. S. Kischuk May 1988

Digital Optical Iterative Pattern Recognizer, Samuel Peter Kozaitis, C. S. Kischuk

Electrical Engineering and Computer Science Faculty Publications

An optical pattern recognizer which classifies an input sequence into one of two classes is described. The language of regular expressions is used to identify a set of input sequences to be recognized. The system is realized without memory elements by using an optical iterative array it with the method of symbolic substitution. The hardware must be able to implement arbitrary and multiple substitution rules for the general design of a pattern recognizer. © 1988 SPIE

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Focused Acoustic Wave (Faw) Channelizer, Dennis R. Pape, Andrew M. Bardos, Marc H. Popek, Manhar L. Shah Sep 1986

Focused Acoustic Wave (Faw) Channelizer, Dennis R. Pape, Andrew M. Bardos, Marc H. Popek, Manhar L. Shah

Electrical Engineering and Computer Science Faculty Publications

The architecture, operation, and performance of a new integrated acoustic RF channelizer are described. The all- acoustic device uses a phased array piezoelectric transducer to generate frequency dispersed bulk acoustic waves over a 500 MHz bandwidth. The waves are focused onto a 25 channel receiver electrode array by a cylindrical reflector formed on the opposing surface of the device. This channelizer has the potential of providing higher dynamic range than competing technologies. © 1986 SPIE.

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