Physical Sciences and Mathematics Commons^™

Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi

Dissertations

Video analysis is an active and rapidly expanding research area in computer vision and artificial intelligence due to its broad applications in modern society. Many methods have been proposed to analyze the videos, but many challenging factors remain untackled. In this dissertation, four statistical modeling methods are proposed to address some challenging traffic video analysis problems under adverse illumination and weather conditions.

First, a new foreground detection method is presented to detect the foreground objects in videos. A novel Global Foreground Modeling (GFM) method, which estimates a global probability density function for the foreground and applies the Bayes decision rule …

Face Recognition Using Multiple Features In Different Color Spaces, Zhiming Liu

Dissertations

Face recognition as a particular problem of pattern recognition has been attracting substantial attention from researchers in computer vision, pattern recognition, and machine learning. The recent Face Recognition Grand Challenge (FRGC) program reveals that uncontrolled illumination conditions pose grand challenges to face recognition performance. Most of the existing face recognition methods use gray-scale face images, which have been shown insufficient to tackle these challenges. To overcome this challenging problem in face recognition, this dissertation applies multiple features derived from the color images instead of the intensity images only.

First, this dissertation presents two face recognition methods, which operate in different …

Solar Activity Detection And Prediction Using Image Processing And Machine Learning Techniques, Gang Fu

Dissertations

The objective of the research in this dissertation is to develop the methods for automatic detection and prediction of solar activities, including prominence eruptions, emerging flux regions and solar flares. Image processing and machine learning techniques are applied in this study. These methods can be used for automatic observation of solar activities and prediction of space weather that may have great influence on the near earth environment.

The research presented in this dissertation covers the following topics: i) automatic detection of prominence eruptions (PBs), ii) automatic detection of emerging flux regions (EFRs), and iii) automatic prediction of solar flares.

In …

Automatic Solar Feature Detection Using Image Processing And Pattern Recognition Techniques, Ming Qu

Dissertations

The objective of the research in this dissertation is to develop a software system to automatically detect and characterize solar flares, filaments and Corona Mass Ejections (CMEs), the core of so-called solar activity. These tools will assist us to predict space weather caused by violent solar activity. Image processing and pattern recognition techniques are applied to this system.

For automatic flare detection, the advanced pattern recognition techniques such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Support Vector Machine (SVM) are used. By tracking the entire process of flares, the motion properties of two-ribbon flares are derived automatically. In …

Handgrip Pattern Recognition, Zong Chen

Dissertations

There are numerous tragic gun deaths each year. Making handguns safer by personalizing them could prevent most such tragedies. Personalized handguns, also called "smart" guns, are handguns that can only be fired by the authorized user. Handgrip pattern recognition holds great promise in the development of the smart gun.

Two algorithms, static analysis algorithm and dynamic analysis algorithm, were developed to find the patterns of a person about how to grasp a handgun. The static analysis algorithm measured 160 subjects' fingertip placements on the replica gun handle. The cluster analysis and discriminant analysis were applied to these fingertip placements, and …

Recursive Soft Morphological Filters, Padmaja Puttagunta

Theses

Mathematical morphology which is based on set-theoretic concept, extracts object features by choosing a suitable structuring shape as a probe. Morphological filters are set operations that transform an image into a quantitative description of its geometrical structure: Appropriately used, they can eliminate noises or irrelevancies while preserv¬ing the details of the original image. The applications of morphological filters in image processing and analysis are numerous, which include shape recognition, industrial parts inspection, nonlinear filtering, and biomedical image processing.

Soft morphological filters are used for smoothing signals with the advantage of being less sensitive to additive noises and to small variations …