Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network

Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics

PDF

Air Force Institute of Technology

Pattern recognition systems

Articles 1 - 16 of 16

Full-Text Articles in Entire DC Network

Computer Aided Multi-Data Fusion Dismount Modeling, Juan L. Morales Mar 2012

Computer Aided Multi-Data Fusion Dismount Modeling, Juan L. Morales

Theses and Dissertations

Recent research efforts strive to address the growing need for dismount surveillance, dismount tracking and characterization. Current work in this area utilizes hyperspectral and multispectral imaging systems to exploit spectral properties in order to detect areas of exposed skin and clothing characteristics. Because of the large bandwidth and high resolution, hyperspectral imaging systems pose great ability to characterize and detect dismounts. A multi-data dismount modeling system where the development and manipulation of dismount models is a necessity. This thesis demonstrates a computer aided multi-data fused dismount model, which facilitates studies of dismount detection, characterization and identification. The system is created …


Overcoming Pose Limitations Of A Skin-Cued Histograms Of Oriented Gradients Dismount Detector Through Contextual Use Of Skin Islands And Multiple Support Vector Machines, Jonathon R. Climer Mar 2011

Overcoming Pose Limitations Of A Skin-Cued Histograms Of Oriented Gradients Dismount Detector Through Contextual Use Of Skin Islands And Multiple Support Vector Machines, Jonathon R. Climer

Theses and Dissertations

This thesis provides a novel visualization method to analyze the impact that articulations in dismount pose and camera aspect angle have on histograms of oriented gradients (HOG) features and eventual detections. Insights from these relationships are used to identify limitations in a state of the art skin cued HOG dismount detector's ability to detect poses not in a standard upright stances. Improvements to detector performance are made by further leveraging available skin information, reducing false detections by an additional order of magnitude. In addition, a method is outlined for training supplemental support vector machines (SVMs) from computer generated data, for …


A Hybrid Templated-Based Composite Classification System, Michael A. Turnbaugh Mar 2009

A Hybrid Templated-Based Composite Classification System, Michael A. Turnbaugh

Theses and Dissertations

An automatic target classification system contains a classifier which reads a feature as an input and outputs a class label. Typically, the feature is a vector of real numbers. Other features can be non-numeric, such as a string of symbols or alphabets. One method of improving the performance of an automatic classification system is through combining two or more independent classifiers that are complementary in nature. Complementary classifiers are observed by finding an optimal method for partitioning the problem space. For example, the individual classifiers may operate to identify specific objects. Another method may be to use classifiers that operate …


Statistical Removal Of Shadow For Applications To Gait Recognition, Brian D. Hockersmith Mar 2008

Statistical Removal Of Shadow For Applications To Gait Recognition, Brian D. Hockersmith

Theses and Dissertations

The purpose of this thesis is to mathematically remove the shadow of an individual on video. The removal of the shadow will aid in the rendering of higher quality binary silhouettes than previously allowed. These silhouettes will allow researchers studying gait recognition to work with silhouettes unhindered by unrelated data. The thesis begins with the analysis of videos of solid colored backgrounds. A formulation of the effect of shadow on specified colors will aid in the derivation of a hypothesis test to remove an individual’s shadow. Video of an individual walking normally, perpendicular to the camera will be utilized to …


Use Of Tabu Search In A Solver To Map Complex Networks Onto Emulab Testbeds, Jason E. Macdonald Mar 2007

Use Of Tabu Search In A Solver To Map Complex Networks Onto Emulab Testbeds, Jason E. Macdonald

Theses and Dissertations

The University of Utah's solver for the testbed mapping problem uses a simulated annealing metaheuristic algorithm to map a researcher's experimental network topology onto available testbed resources. This research uses tabu search to find near-optimal physical topology solutions to user experiments consisting of scale-free complex networks. While simulated annealing arrives at solutions almost exclusively by chance, tabu search incorporates the use of memory and other techniques to guide the search towards good solutions. Both search algorithms are compared to determine whether tabu search can produce equal or higher quality solutions than simulated annealing in a shorter amount of time. It …


Statistical Approach To Background Subtraction For Production Of High-Quality Silhouettes For Human Gait Recognition, Jennifer J. Samler Sep 2006

Statistical Approach To Background Subtraction For Production Of High-Quality Silhouettes For Human Gait Recognition, Jennifer J. Samler

Theses and Dissertations

This thesis uses a background subtraction to produce high-quality silhouettes for use in human identification by human gait recognition, an identification method which does not require contact with an individual and which can be done from a distance. A statistical method which reduces the noise level is employed resulting in cleaner silhouettes which facilitate identification. The thesis starts with gathering video data of individuals walking normally across a background scene. From there the video is converted into a sequence of images that are stored as joint photographic experts group (jpeg) files. The background is subtracted from each image using a …


An Analysis Of Perturbed Quantization Steganography In The Spatial Domain, Matthew D. Spisak Mar 2005

An Analysis Of Perturbed Quantization Steganography In The Spatial Domain, Matthew D. Spisak

Theses and Dissertations

Steganography is a form of secret communication in which a message is hidden into a harmless cover object, concealing the actual existence of the message. Due to the potential abuse by criminals and terrorists, much research has also gone into the field of steganalysis - the art of detecting and deciphering a hidden message. As many novel steganographic hiding algorithms become publicly known, researchers exploit these methods by finding statistical irregularities between clean digital images and images containing hidden data. This creates an on-going race between the two fields and requires constant countermeasures on the part of steganographers in order …


Daytime Detection Of Space Objects, Alistair D. Funge Mar 2005

Daytime Detection Of Space Objects, Alistair D. Funge

Theses and Dissertations

Space Situational Awareness (SSA) requires repeated object updates for orbit accuracy. Detection of unknown objects is critical. A daytime model was developed that evaluated sun flares and assessed thermal emissions from space objects. Iridium satellites generate predictable sun glints. These were used as a model baseline for daytime detections. Flares and space object thermal emissions were examined for daytime detection. A variety of geometric, material and atmospheric characteristics affected this daytime detection capability. In a photon noise limited mode, simulated Iridium flares were detected. The peak Signal-to- Noise Ratios (SNR) were 6.05e18, 9.63e5, and 1.65e7 for the nighttime, daytime and …


Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver Sep 2004

Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver

Theses and Dissertations

A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stochastic objective functions and a mixture of design variable types. The generalized pattern search (GPS) class of algorithms is extended to a new problem setting in which objective function evaluations require sampling from a model of a stochastic system. The approach combines GPS with ranking and selection (R&S) statistical procedures to select new iterates. The derivative-free algorithms require only black-box simulation responses and are applicable over domains with mixed variables (continuous, discrete numeric, and discrete categorical) to include bound and linear constraints on …


Categorizing Network Attacks Using Pattern Classification Algorithms, George E. Noel Iii Mar 2002

Categorizing Network Attacks Using Pattern Classification Algorithms, George E. Noel Iii

Theses and Dissertations

The United States Air Force relies heavily on computer networks for many day-to-day activities. Many of these networks are affected by various types of attacks that can be launched from anywhere on the globe. The rising prominence of organizations such as the AFCERT and the MAJCOM NOSCs is evidence of an increasing realization among the Air Force leadership that protecting our computer networks is vitally important. A critical requirement for protecting our networks is the ability to detect attacks and intrusion attempts. This research is an effort to refine a portion of an AFIT-developed intrusion detection system known as the …


A Distributed Agent Architecture For A Computer Virus Immune System, Paul K. Harmer Mar 2000

A Distributed Agent Architecture For A Computer Virus Immune System, Paul K. Harmer

Theses and Dissertations

Information superiority is identified as an Air Force core competency and is recognized as a key enabler for the success of future missions. Information protection and information assurance are vital components required for achieving superiority in the Infosphere, but these goals are threatened by the exponential birth rate of new computer viruses. The increased global interconnectivity that is empowering advanced information systems is also increasing the spread of malicious code and current anti-virus solutions are quickly becoming overwhelmed by the burden of capturing and classifying new viral stains. To overcome this problem, a distributed computer virus immune system (CVIS) based …


Weighted Mahalanobis Distance For Hyper-Ellipsoidal Clustering, Khaled S. Younis Dec 1996

Weighted Mahalanobis Distance For Hyper-Ellipsoidal Clustering, Khaled S. Younis

Theses and Dissertations

Cluster analysis is widely used in many applications, ranging from image and speech coding to pattern recognition. A new method that uses the weighted Mahalanobis distance (WMD) via the covariance matrix of the individual clusters as the basis for grouping is presented in this thesis. In this algorithm, the Mahalanobis distance is used as a measure of similarity between the samples in each cluster. This thesis discusses some difficulties associated with using the Mahalanobis distance in clustering. The proposed method provides solutions to these problems. The new algorithm is an approximation to the well-known expectation maximization (EM) procedure used to …


Spatio-Temporal Pattern Recognition Using Hidden Markov Models, Kenneth H. Fielding Jun 1994

Spatio-Temporal Pattern Recognition Using Hidden Markov Models, Kenneth H. Fielding

Theses and Dissertations

A new spatio-temporal method for identifying 3D objects found in 2D image sequences is presented. The Hidden Markov Model technique is used as a spatio-temporal classification algorithm to identify 3D objects by the temporal changes in observed shape features. A new information theoretic argument is developed that proves identifying objects based on image sequences can lead to higher classification accuracies than single look methods. A new distance measure is proposed that analyzes the performance of Hidden Markov Models in a multi-class pattern recognition problem. A three class problem identifying moving light display objects provides experimental verification of the sequence processing …


Subgrouped Real Time Recurrent Learning Neural Networks, Jeffrey S. Dean May 1994

Subgrouped Real Time Recurrent Learning Neural Networks, Jeffrey S. Dean

Theses and Dissertations

A subgrouped Real Time Recurrent Learning (RTRL) network was evaluated. The one layer net successfully learns the XOR problem, and can be trained to perform time dependent functions. The net was tested as a predictor on the behavior of a signal, based on past behavior. While the net was not able to predict the signal's future behavior, it tracked the signal closely. The net was also tested as a classifier for time varying phenomena; for the differentiation of five classes of vehicle images based on features extracted from the visual information. The net achieved a 99.2% accuracy in recognizing the …


A Non-Homogeneous, Spatio-Temporal, Wavelet Multiresolution Analysis And Its Application To The Analysis Of Motion, Thomas J. Burns Dec 1993

A Non-Homogeneous, Spatio-Temporal, Wavelet Multiresolution Analysis And Its Application To The Analysis Of Motion, Thomas J. Burns

Theses and Dissertations

This research presents a multiresolution wavelet analysis tool for analyzing motion in time sequential imagery. A theoretical framework is developed for constructing an L2R wavelet multiresolution analysis from three non-identical spatial and temporal L2R wavelet multiresolution analyses. This framework provides the flexibility to tailor the spatio-temporal frequency characteristics of the three dimensional wavelet filter to match the frequency behavior of the analyzed signal. An unconventional, discrete multiresolution wavelet decomposition algorithm is developed which yields a rich set of independent spatio-temporally oriented frequency channels for analyzing, the size and speed characteristics of moving objects. Unlike conventional wavelet decomposition methods, this algorithm …


Handwritten Word Recognition Based On Fourier Coefficients, Gary F. Shartle Dec 1993

Handwritten Word Recognition Based On Fourier Coefficients, Gary F. Shartle

Theses and Dissertations

A machine which can read unconstrained words remains an unsolved problem. For example, automatic entry o handwritten documents into a computer is yet to be accomplished. Most systems attempt to segment letters o a word and read words one character at a time. Segmenting a handwritten word is very difficult and often, the confidence of the results is low. Another method which avoids segmentation altogether is to treat each word as a whole. This research investigates the use of Fourier Transform coefficients, computed from the whole word, for the recognition of handwritten words. To test this concept, the particular pattern …