Engineering Commons^™

Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda

Dissertations

The removal of atmospheric turbulence (AT) distortion in long range imaging is one of the most challenging areas of research in imaging processing with an immediate need for solutions in several applications such as in military and transportation systems. AT exacerbates distortion due to non-linear geometric blur and scintillations in long-distance images and videos, severely reducing image quality and information interpretation. AT negatively impacts both human and computer vision systems, compromising visibility essential for accurate object identification and tracking.

In this dissertation, a novel sparse analysis framework is developed to address efficient AT blur and scintillation removal in video. Operating …

Vision-Based Framework For Monitoring Of Eating Behavior Of Persons With Alzheimer’S Disease, Haitham Al-Anssari

Dissertations

Dementia is a syndrome used to describe an array of significant declines in cognitive abilities due to progressive and irreversible loss of neurons and brain functioning. This neurodegeneration seriously affects daily life activities like driving, shopping, working and speaking. Among these, Alzheimer’s disease is the most common type of dementia, with individuals experiencing loss of memory and thinking and reasoning skills. Due to cognitive decline, individuals with Alzheimer’s often suffer from malnutrition, since they do not eat, even when food is presented, and must be fed with assistance. This assistance presents a significant burden of time to caregivers, and consequently …

Face Recognition With Multi-Stage Matching Algorithms, Xianming Chen

Dissertations

For every face recognition method, the primary goal is to achieve higher recognition accuracy and spend less computational costs. However, as the gallery size increases, especially when one probe image corresponds to only one training image, face recognition becomes more and more challenging. First, a larger gallery size requires more computational costs and memory usage. Meanwhile, that the large gallery sizes degrade the recognition accuracy becomes an even more significant problem to be solved.

A coarse parallel algorithm that equally divides training images and probe images into multiple processors is proposed to deal with the large computational costs and huge …

A Discriminative Imaging-Based Framework For Road Sign Condition Assessment Using Local Features And Svm Classifiers, Jafar Jameel Abukhait

Dissertations

Transportation departments are required to monitor the condition of road signs through appropriate condition assessment mechanisms to improve road safety and keep drivers properly informed. Typically, these mechanisms include visual inspection or specialized equipment such as retroreflectometers. These methods are costly, tedious, and risky since they need direct contact with road signs. Efforts to use emerging computer vision techniques for the assessment of road signs condition combined with the availability of road data inventories are allowing the automation of these processes, thus easing the inspection process, reducing costs of equipment, and decreasing the risks associated with the need for maintenance …