Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2003. / Thesis advisor(s): Phillip E. Pace, Don Brutzman. Includes bibliographical references (p. 129-130). Also available online.

Includes bibliographical references (p. 51-57).

Includes bibliographical references (p. 59-66).

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2003. / Thesis advisor(s): Douglas J. Fouts, Phillip E. Pace. Includes bibliographical references (p. 143-144). Also available online.

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xiii, 102 p.: ill. (some col.). Includes abstract and vita. Advisor: Roger A. Crawfis, Dept. of Computer and Information Science. Includes bibliographical references (p. 98-102).

By applying the image processing algorithms used in surveillance systems on video data obtained from a web camera, a motion detection application can be created and incorporated into web based games. The use of motion detection opens up a vast field of new possibilities in game design and this thesis will therefore cover how to create a motion detection JavaScript module which can be used in web based games. The performance and quality of the motion detection algorithms are important to consider when creating an application. What motion detection algorithms can be used to give a qualitativerepresentation without affecting the performance of a web based game will be analyzed and implemented in this thesis. Since the performance of the Central Processing Unit will not suffice, WebGL and the parallelism of the Graphical Processing Unit will be utilized to implement some of the most recognized image processing algorithms used in motion detection systems. The work resulted in an application where Gaussian blur and Frame Subtraction were used to detect and return areas where motion has been detected.

Traditional geometric scene analysis cannot attempt to address the understanding of human vision. Instead it adopts an algorithmic approach, concentrating on geometric model fitting. Human vision, however, is both quick and accurate but very little is known about how the recognition of objects is performed with such speed and efficiency. It is thought that there must be some process both for coding and storage which can account for these characteristics. In this thesis a more strict emulation of human vision, based on work derived from medical psychology and other fields, is proposed. Human beings must store perceptual information from which to make comparisons, derive structures and classify objects. It is widely thought by cognitive psychologists that some form of symbolic representation is inherent in this storage. Here a mathematical syntax is defined to perform this kind of symbolic description. The symbolic structures must be capable of manipulation and a set of operators is defined for this purpose. The early visual cortex and geniculate body are both inherently parallel in operation and simple in structure. A broadly connectionist emulation of this kind of structure is described, using independent computing elements, which can perform segmentation, re-colouring and generation of the base elements of the description syntax. Primal colour information is then collected by a second network which forms the visual topology, colouring and position information of areas in the image as well as a full description of the scene in terms of a more complex symbolic set. The idea of different visual contexts is introduced and a model is proposed for the accumulation of context rules. This model is then applied to a database of natural images.

This thesis discusses certain aspects of the noninvasive imaging technique known as optical coherence tomography (OCT). Topics include three-dimensional image rendering as well as application of the Fast Fourier Transform to reconstruct the axial scan as a function of depth. Implementations use LabVIEW system design software and a Xilinx Spartan-6 field-programmable gate array (FPGA). The inherent parallel-processing capability of an FPGA opens the possibility of designing a "super-sensor" which entails simultaneous capturing of image and sensor data, giving medical practitioners more data for potentially improved diagnosis. FPGA-based processing would benefit many methods of characterizing biological samples; OCT and photonic crystal microarray biosensors are discussed. / text

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy