Electrical and Computer Engineering Commons^™

A Multiplier-Less Architecture For High Speed Computation Of Multi-Dimensional Convolution, Ming Zhu Zhang

Electrical & Computer Engineering Theses & Dissertations

One of the most computationally intensive operations in digital image/video processing systems is multi-dimensional convolution. Every image/video processor needs the convolution module in its pre-processing stage. Fast and efficient design of the convolution module in an application specific system is a great challenge in VLSI (Very Large Scale Integration) design. Convolution operator requires a large set of multipliers and accumulators. A high precision multiplier takes enormous amount of VLSI area and it consumes more power. Hence reduction of the number of multipliers is another important challenge in VLSI design. A multiplier-less architecture for the design of a multi-dimensional convolution module …

Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation And Aliasing Artifact Mitigation, Jonathan E. Luminati

Theses and Dissertations

Traditional monostatic Synthetic Aperture Radar (SAR) platforms force the user to choose between two image types: larger, low resolution images or smaller, high resolution images. Switching to a Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR) approach allows formation of large high-resolution images. Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. Inverse SAR (ISAR) imagery from a Radar Cross Section (RCS) chamber validates this approach. …

Optimization Of Automatic Target Recognition With A Reject Option Using Fusion And Correlated Sensor Data, Trevor I. Laine

Theses and Dissertations

This dissertation examines the optimization of automatic target recognition (ATR) systems when a rejection option is included. First, a comprehensive review of the literature inclusive of ATR assessment, fusion, correlated sensor data, and classifier rejection is presented. An optimization framework for the fusion of multiple sensors is then developed. This framework identifies preferred fusion rules and sensors along with rejection and receiver operating characteristic (ROC) curve thresholds without the use of explicit misclassification costs as required by a Bayes' loss function. This optimization framework is the first to integrate both "vertical" warfighter output label analysis and "horizontal" engineering confusion matrix …

Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham

Theses and Dissertations

The structure from motion process creates three-dimensional models from a sequence of images. Until recently, most research in this field has been restricted to land-based imagery. This research examines the current methods of land-based structure from motion and evaluates their performance for aerial imagery. Current structure from motion algorithms search the initial image for features to track though the subsequent images. These features are used to create point correspondences between the two images. The correspondences are used to estimate the motion of the camera and then the three-dimensional structure of the scene. This research tests current algorithms using synthetic data …

Utilizing Near-Field Measurements To Characterize Far-Field Radar Signatures, John R. Watkins

Theses and Dissertations

The increased need for stealth aircraft requires an on-site Far-Field (FF) Radar Cross-Section (RCS) measurement process. Conducting these measurements in on-site Near-Field (NF) monostatic facilities results in significant savings for manufacturers and acquisition programs. However, NF measurements are not directly extended to a FF RCS. Therefore, a large target Near-Field to Far-Field Transformation (NFFFT) is needed for RCS measurements. One approach requires an Inverse Synthetic Aperture Radar (ISAR) process to create accurate scattering maps. The focus of this work is the development of accurate NF scattering maps generated by a monostatic ISAR process. As a first look, the process is …

Target Recognition Using Late-Time Returns From Ultra-Wideband, Short-Pulse Radar, Kenneth J. Pascoe

Theses and Dissertations

The goal of this research is to develop algorithms that recognize targets by exploiting properties in the late-time resonance induced by ultra-wide band radar signals. A new variant of the Matrix Pencil Method algorithm is developed that identifies complex resonant frequencies present in the scattered signal. Kalman filters are developed to represent the dynamics of the signals scattered from several target types. The Multiple Model Adaptive Estimation algorithm uses the Kalman filters to recognize targets. The target recognition algorithm is shown to be successful in the presence of noise. The performance of the new algorithms is compared to that of …

Data Smoothing And Interpolation Using Eighth-Order Algebraic Splines, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

A new type of algebraic spline is used to derive a filter for smoothing or interpolating discrete data points. The spline is dependent on control parameters that specify the relative importance of data fitting and the derivatives of the spline. A general spline of arbitrary order is first formulated using matrix equations. We then focus on eighth-order splines because of the continuity of their first three derivatives (desirable for motor and robotics applications). The spline's matrix equations are rewritten to give a recursive filter that can be implemented in real time for lengthy data sequences. The filter is lowpass with …

Discovering The Merit Of The Wavelet Transform For Object Classification, Matthew D. Eyster

Theses and Dissertations

Vision is the primary sense by which most biological systems collect information about their environment. Computer vision is a branch of artificial intelligence concerned with endowing machines with the ability to understand images. Object recognition is a key part of machine vision with far reaching benefits ranging from target recognition, surveillance systems, to automation systems. Extraction of salient features from an image is one of the key steps in object recognition. Typically, geometric primitives are extracted from an image using local analysis. However, the wavelet transform provides a global approach with good locality. Additionally, the directional and multiresolution properties may …

Reconstruction Algorithm Characterization And Performance Monitoring In Limited-Angle Chromotography, Kevin C. Gustke

Theses and Dissertations

Hyperspectral data collection and analysis is an increasing priority with the growing need to obtain greater classification precision than offered by traditional spatial imagery. In this thesis, trends in hyperspectral chromotomographic reconstruction are explored where reconstruction is performed using a series of spatial-chromatic images. Chromotomography involves capturing a series of two-dimensional images where each image is created by placing a prism in front of the focal plane array; causing spectral dispersion corresponding to a series of prism angles over a single rotation. Before testing reconstruction, synthetic data is produced, approximating what would be produced from prism dispersion on the focal …

Autonomous Robotic Automation Systemwith Vision Feedback, Jeffery Rosino

Electronic Theses and Dissertations

In this thesis, a full design, development and application of an autonomous robotic automation system using vision feedback is performed. To realize this system, a cylindrical manipulator configuration is implemented, using a personal computer (PC) based PID controller from National Instruments. Full autonomous control will be achieved via a programmable human machine interface (HMI) developed on a PC using Borland C++ Builder. The vision feedback position control is accomplished using an ordinary "off-the-shelf" web camera. The manuscript is organized as follows; After Chapter 1, an introduction to automation history and its role in the manufacturing industry, Chapter 2 discusses and …

Cmos Digital Pixel Sensor Array With Time Domain Analogue To Digital Conversion, Alistair J. Kitchen

Theses: Doctorates and Masters

This thesis presents a digital pixel sensor array, which is the first stage of an ongoing project to produce a CMOS image sensor with on-chip image processing. The analogue to digital conversion is performed at the pixel level, with the result stored in pixel memory. This architecture allows fast, reliable access to the image data and simplifies the integration of the image array and the processing logic. Each pixel contains a photodiode sensor, a comparator, memory and addressing logic. The photodiode sensor operates in integrating mode, where the photodiode junction capacitance is first charged to an initial voltage, and then …

Primitives And Design Of The Intelligent Pixel Multimedia Communicator, David K. Lucas

Theses: Doctorates and Masters

Communication systems arc an ever more essential component of our modern global society. Mobile communications systems are still in a state of rapid advancement and growth. Technology is constantly evolving at a rapid pace in ever more diverse areas and the emerging mobile multimedia based communication systems offer new challenges for both current and future technologies. To realise the full potential of mobile multimedia communication systems there is a need to explore new options to solve some of the fundamental problems facing the technology. In particular, the complexity of such a system within an infrastructure framework that is inherently limited …

Classification Of Radar Targets Using Invariant Features, Gregory J. Meyer

Theses and Dissertations

Automatic target recognition ATR using radar commonly relies on modeling a target as a collection of point scattering centers, Features extracted from these scattering centers for input to a target classifier may be constructed that are invariant to translation and rotation, i.e., they are independent of the position and aspect angle of the target in the radar scene. Here an iterative approach for building effective scattering center models is developed, and the shape space of these models is investigated. Experimental results are obtained for three-dimensional scattering centers compressed to nineteen-dimensional feature sets, each consisting of the singular values of the …

A Pipelined Architecture For Real Time Correction Of Barrel Distortion In Wide-Angle Camera Images, Hau Trung Ngo

Electrical & Computer Engineering Theses & Dissertations

Images captured by wide-angle cameras show barrel type spatial distortion due to wide-angle configuration of the camera lens where image regions farther from the center are compressed in a nonlinear fashion. The barrel distortion correction technique based on least squares estimation attempts to correct a distorted image by expanding it nonlinearly so that straight lines in the object space remain straight in the image space. The intensity value of a pixel in the expanded image is calculated by back mapping its position to the corresponding position in the distorted image and performing linear interpolation on the neighboring pixels. Distorted images …

Adaptive Segmentation Techniques For Object Region Extraction From Images With Complex Lighting Environment, Deepthi P. Valaparla

Electrical & Computer Engineering Theses & Dissertations

Automated image segmentation of objects in complex lighting environments is a difficult task since it is not possible to pre-define a threshold to distinguish the object from the background. It is ascertained that an effective threshold citation for such objects depends on the negative binomial distribution of the object region with respect to the background lighting. Based on this concept, a novel adaptive threshold selection method for automatic segmentation of the lumen region in endoscopic images is presented in this thesis. More precise lumen region and boundary are obtained by an integrated neighborhood search based region growing procedure whose speed …

Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration, Daniel L. Ward

Theses and Dissertations

The limited resolution of video imagery taken by aircraft, over geographical areas of interest, hinders the accurate extraction of useful information. The frame resolution of the video is determined by the camera that created it. Information exists about the camera which can be used to increase frame resolution beyond the resolution capability of the camera. This is achieved by a process called super-resolution, which uses multiple low-resolution video frames to create one high-resolution image.

Feature Guided Image Registration Applied To Phase And Wavelet-Base Optic Flow, Kate R. Duffy

Theses and Dissertations

Optic Flow algorithms are useful in problems such as computers vision, navigational systems, and robotics. However, current algorithms are computationally expensive or lack the accuracy to be effective compared with traditionally navigation systems. Recently, lower accuracy inertial navigation systems (INS) based on Microelectromechanical systems (MEMS) technology have been proposed to replace more accurate traditional navigation systems.

Fast Compression Of Imagery With High Frequency Content, D. Scott Anderson

Theses and Dissertations

Image compression is an active area due to the many applications involving electronic media. Much research has been focused on image quality versus bit rate and/or algorithm speed. Here, we seek an effective image coder with a weighted constraint on speed. However, the compression must not taint the quality of impulsive features on the image. Moreover, the camera is operated in a mode that creates a dominant fixed pattern noise across the image array, degrading visual quality and disrupting compression performance. We propose a method that efficiently compresses such an image. We begin by characterizing and removing the fixed pattern …

Stereo Matching Algorithm By Propagation Of Correspondences And Stereo Vision Instrumentation, Peerajak Witoonchart

Theses

A new image processing method is described for measuring the 3-D coordinates of a complex, biological surface. One of the problems in stereo vision is known as the accuracy-precision tradeoff problem. This thesis proposes a new method that promises to solve this problem. To do so, two issues are addressed. First, stereo vision instrumentation methods are described. This instrumentation includes a camera system as well as camera calibration, rectification, matching and triangulation. Second, the approach employs an array of cameras that allow accurate computation of the depth map of a surface by propagation of correspondences through pair-wise camera views.

The …

Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra

Theses and Dissertations

The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …

Interactive Virtual Laboratory For Experience With A Smart Bridge Test, Elizabeth C. Eckhoff, Vicki M. Eller, Steve Eugene Watkins, Richard Hall

Electrical and Computer Engineering Faculty Research & Creative Works

Virtual laboratory experiments can be cost effective, convenient instructional resources that have appeal to a wide range of learning styles. Expensive, time-consuming laboratory tests can be experienced repeatedly and remotely using interactive simulations and original video footage or animations. A virtual experiment can incorporate meaningful exercises, procedural options, and background hyperlinks to create a comprehensive "hands on" environment. Also, it may be used as preliminary training for the actual experiment.

An interactive LabVIEW-based laboratory for a load test simulation of an existing demonstration bridge was created. This smart truss bridge is instrumented with fiber optic strain sensors situated on the …

Image Registration Using Redundant Wavelet Transforms, Richard K. Brown

Theses and Dissertations

Imagery is collected much faster and in significantly greater quantities today compared to a few years ago. Accurate registration of this imagery is vital for comparing the similarities and differences between multiple images. Since human analysis is tedious and error prone for large data sets, we require an automatic, efficient, robust, and accurate method to register images. Wavelet transforms have proven useful for a variety of signal and image processing tasks, including image registration. In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and …

An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga

Theses and Dissertations

Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This thesis evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentors. This objective comparison uses a multi-metric a approach with a set of …

Neural Networks Versus Nonparametric Neighbor-Based Classifiers For Semisupervised Classification Of Landsat Thematic Mapper Imagery, Perry J. Hardin

Faculty Publications

Semisupervised classification is one approach to converting multiband optical and infrared imagery into landcover maps. First, a sample of image pixels is extracted and clustered into several classes. The analyst next combines the clusters by hand to create a smaller set of groups that correspond to a useful landcover classification. The remaining image pixels are then assigned to one of the aggregated cluster groups by use of a per-pixel classifier. Since the cluster aggregation process frequently creates groups with multivariate shapes ill suited for parametric classifiers, there has been renewed interest in nonparametric methods for the task. This research reports …

Knowledge-Based Navigation For Autonomous Road Vehicles, Murat Eki̇nci̇, Franches W.J.Gibbs, Barry T. Thomas

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a computer vision system for an autonomous road vehicle (ARV) that is capable of negotiating complex road networks including road junctions in real time. The ultimate aim of the system is to enable the vehicle to drive automatically along a given complex road network whose geometric description is known. This computer vision system includes three main techniques which are necessary for an ARV: a) road following, b) road junction detection, c) manoeuvring at the road junction. The road following algorithm presents a method of executing a number of algorithms using different methods concurrently, fusing their outputs together …

Detection And Robustness Of Digital Image Watermarking Signals : A Communication Theory Approach, George F. Elmasry

Dissertations

The detection and robustness of the watermark signal is studied from a communications point of view. The contributions of this dissertation are presented in two parts. The first part, which covers the detection aspect, introduces a new digital image watermarking approach that embeds meaningful information in a copyright protection watermark signal; demonstrates the need to approach the watermark signal as a power-constrained signal; studies the relationship between the watermark signal dimension and the image capacity to the signal; explains the similarities and differences between detecting the watermark signal and detecting a signal over a spread-spectrum communication channel; and analyzes the …

Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson

Theses and Dissertations

Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …

Evaluation Of A Maximum A-Posteriori Slope Estimator For A Hartmann Wavefront Sensor, Troy B. Van Caster

Theses and Dissertations

Current methods for estimating the wavefront slope at the aperture of a telescope using a Hartmann wavefront sensor are based upon a centroid shift estimator. The centroid shift estimator determines the displacement, or shift, of the centroid off the optical axis using a moment calculation of the intensity distributions recorded in each subaperture. This centroid shift is proportional to the average slope of the wavefront in each subaperture. A maximum a-posteriori (MAP) slope estimator takes advantage of a-priori knowledge of the wavefront slope statistics and total irradiance falling on the subaperture detector arrays when determining the shift estimate. In order …

Joint-Transform Correlator Architecture For Wavelet Feature Extraction, Samuel Peter Kozaitis, Mark A. Getbehead, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

A version of an image consisting of multiple wavelet scales allows for more flexible feature extraction when compared to the use of one wavelet scale. We proposed an imaging system based on a multiple-input joint-transform correlator, that could be used for multiple wavelet-scale analysis of an input image. Given a single input image and wavelet, for m wavelet scales, m versions of the wavelet and m copies of the input image were generated using conventional optics that are used as inputs to a joint wavelet-transform correlator. The output consisted of 4 m - 1 correlation results, one of which is …

Multispectral Image Feature Extraction By The Joint Wavelet-Transform Correlator, Samuel Peter Kozaitis, Mark A. Getbehead, Wesley E. Foor

Electrical Engineering and Computer Science Faculty Publications

A multispectral version of an image consisting of multiple wavelet components allows for more flexible feature extraction when compared to the use of one wavelet component. We showed how a multiple-input joint wavelet- transform correlator could be used for multispectral analysis of an input image. For m wavelet scales, m versions of the wavelet and m copies of the input image were generated using conventional optics that are used as inputs to a joint wavelet-transform correlator. The output consisted of 4m-1 correlation results, one of which is the desired output. The space-bandwidth product of the system is the same as …