Optical coherence tomography (OCT), being a noninvasive imaging modality, has begun to find vast use in the diagnosis and management of retinal diseases. These high-resolution images of the retina allow structural changes to be detected and tracked. For instance, in glaucoma, the retinal nerve fiber layer (RNFL) has been known to thin. The recent availability of the considerably larger volumetric data from the spectral-domain OCT scanners has further increased the need for new processing techniques. This body of work is centered around an automated 3-D graph-theoretic approach for the segmentation of 7 surfaces (6 layers) of the retina from 3-D spectral-domain OCT images centered on the optic nerve head (ONH). The multiple surfaces are detected through the computation of a minimum-cost closed set in a vertex-weighted graph constructed using edge/regional information, and subject to a priori determined varying surface interaction and smoothness constraints. The method also addresses the challenges posed by presence of the neural canal and the large blood vessels found at the ONH. The method was used to study RNFL thickness maps of normal and glaucomatous eyes, which showed average thicknesses of 73.72 +/- 32.72um and 60.38 +/- 25.22um (p < 0.01), respectively.

Design and performance of fully-printed Ku-band aperture coupled patch antennas fabricated by a direct digital manufacturing (DDM) approach that integrates fused deposition modeling (FDM) of acrylonitrile butadiene styrene (ABS) thermoplastic with in-situ micro-dispensing of conductive silver paste (CB028) are reported. Microstrip line characterizations are performed and demonstrate that misalignment of ABS substrate deposition direction with microstrip line micro-dispensing direction can degrade the effective conductivity up to 60% within the Ku-band, and must be taken into consideration in antenna array feed network designs. Specically, over 125 µm thick ABS substrate, RF loss of 0.052 dB/mm is obtained at 18 GHz, demonstrating the feasibility of additively manufactured RF devices within the Ku-band. By varying ABS inll ratios and resorting to multi-layer printing with custom substrate thicknesses, single and stacked patch antennas are designed, fabricated, and characterized with bandwidth performances up to 35%, and radiation efficiencies up to 90%. This extensive utilization of the design flexibilities provided by the direct digital manufacturing (i.e. customized substrate thicknesses, multiple substrates with varying infill ratios, and in-situ micro-dispensing of conductors) distinguishes the present work from the recently reported 3-D printed antennas. Compared to the existing work in literature, the antennas presented within this thesis stand out as being fully printed structures, operating in higher frequency range (i.e. Ku-band), and exhibiting high radiation efficiencies with wide bandwidth performances.

Drilled shafts are cylindrical, cast-in-place concrete deep foundation elements. Their construction involves drilled excavation of soil or rock using large diameter augers, and placement of the necessary reinforcing steel in the excavation followed by concreting. Where a high water table is encountered, drilling slurry is used to support the excavation walls and concreting is tremie-placed. Even though the history of drilled shaft construction goes back to the 1950s, the occurrence of anomalies persists in the form of soil inclusions, reduction in shaft cross-sectional area and exposure of reinforcement. One of the main reasons for the anomalies is attributed to the kinematics of concrete flowing radially from within the reinforcing cage to the surrounding annulus/concrete cover region. In view of this radial component of concrete flow and thus radially flowing interfaces between the concrete and slurry, the region outside the cage is more likely to contain veins of poorly cemented or high water-cement ratio material. These veins contain trapped slurry, which oftentimes consists of bentonite, jeapordizing the integrity of the shafts. This research program focuses on the numerical evaluation of self-consolidating concrete (SCC) for drilled shaft application by taking into account realistic non-Newtonian concrete flow properties and the shaft structural blockages. For this objective, a 3-D computational fluid dynamics (CFD) model of the concrete flow in the shaft excavation is developed in ANSYS-Fluent. As a precursor to 3-D modeling, 2-D CFD modeling is carried out using COMSOL Multiphysics. In both 2-D and 3-D models, the Volume of Fluid method is used for computing the motion of the interface between the concrete and the drilling slurry. The models predict the flow patterns and volume fraction of concrete and slurry. The results are encouraging as the flow pattern from the simulation shows both horizontal and vertical creases in the concrete cover region. Moreover the flow pattern shows the concrete head differential developed between the inside and the outside the reinforcement cage. Further, the 3-D model is evaluated by studying the influence of the size of drilled shaft and arrangement of the bars and the results obtained are realistic. With this 3-D model developed as a tool, the simulation of SCC and the normal standard concrete (NC) flow in drilled shaft concreting are studied in terms of creases and concrete head differential encountered in the flow. From the simulation, it is observed that in the flow pattern of SCC, the creases are very few compared to the one obtained from the flow pattern of NC. Moreover, the concrete head differential in the flow pattern of SCC is much less, than the head differential obtained from the flow pattern of NC flow. In the case of SCC, the head differential encountered about one inch. In the case of NC, the concrete head differential is 4-inch when the vertical rebars are spaced at 7-inch apart and 10-inch when the rebars are placed at 3.5-inch apart. Based on this numerical evaluation of SCC flow in the drilled shaft excavation, it is concluded that the performance of SCC is better than the performance of NC in filling the cover annular region of drilled shafts.

<p>The objective of this master thesis was to study the performance of an active triangulation system for 3-D imaging in underwater applications. Structured light from a 20 mW laser and a conventional video camera was used to collect data for generation of 3-D images. Different techniques to locate the laser line and transform it into spatial coordinates were developed and evaluated. A field- and a laboratory trial were performed.</p><p>From the trials we can conclude that the distance resolution is much higher than the lateral- and longitudinal resolution. The lateral resolution can be improved either by using a high frame rate camera or simply by using a low scanning speed. It is possible to obtain a range resolution of less than a millimeter. The maximum range of vision was 5 meters under water measured on a white target and 3 meters for a black target in clear sea water. These results are however dependent on environmental and system parameters such as laser power, laser beam divergence and water turbidity. A higher laser power would for example increase the maximum range.</p>

This paper reviews a number of aspects of visual motion analysis in biological systems from a computational perspective. We illustrate the kinds of insights that have been gained through computational studies and how these observations can be integrated with experimental studies from psychology and the neurosciences to understand the particular computations used by biological systems to analyze motion. The particular areas of motion analysis that we discuss include early motion detection and measurement, the optical flow computation, motion correspondence, the detection of motion discontinuities, and the recovery of three-dimensional structure from motion.

Perceptual studies suggest that the visual system uses the "rigidity" assumption to recover three dimensional structures from motion. Ullman (1984) recently proposed a computational scheme, the incremental rigidity scheme, which uses the rigidity assumptions to recover the structure of rigid and non-rigid objects in motion. The scheme assumes the input to be discrete positions of elements in motion, under orthographic projection. We present formulations of Ullmans' method that use velocity information and perspective projection in the recovery of structure. Theoretical and computer analyses show that the velocity based formulations provide a rough estimate of structure quickly, but are not robust over an extended time period. The stable long term recovery of structure requires disparate views of moving objects. Our analysis raises interesting questions regarding the recovery of structure from motion in the human visual system.

All plane curves can be described at an abstract level by a sequence of five primitive elemental shapes, called "condons", which capture the sequential relations between the singular points of curvature. The condon description provides a basis for enumerating all smooth 2D curves. Let each of these smooth plane be considered as the si lhouette of an opaque 3D object. Clearly an in finity of 3D objects can generate any one of ou r "condon" silhouettes. How then can we p redict which 3D object corresponds to a g iven 2D silhouette? To restrict the infinity of choices, we impose three mathematical properties of smooth surfaces plus one simple viewing constraint. The constraint is an extension of the notion of general position, and seems to drive our preferred inferences of 3D shapes, given only the 2D contour.

This paper continues our work on visual representation s of three-dimensional surfaces [Brady and Yuille 1984b]. The theoretical component of our work is a study of classes of surface curves as a source of constraint n the surface on which they lie, and as a basis for describing it. We analyze bounding contours, surface intersections, lines of curvature, and asymptotes. Our experimental work investigates whether the information suggested by our theoretical study can be computed reliably and efficiently. We demonstrate algorithms that compute lines of curvature of a (Gaussian smoothed) surface; determine planar patches and umbilic regions; extract axes of surfaces of revolution and tube surfaces. We report preliminary results on adapting the curvature primal sketch algorithms of Asada and Brady [1984] to detect and describe surface intersections.

Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

This thesis develops a GIS-based Bayesian approach for area-wide traffic crash analysis. Five years of crash data from Houston, Texas, are analyzed using a geographic information system (GIS), and spatial-temporal patterns of relative crash risk are identified based on a hierarchical Bayesian approach. This Bayesian approach is used to filter the uncertainty in the data and identify and rank roadway segments with potentially high relative risks for crashes. The results provide a sound basis to take preventive actions to reduce the risks in these segments. To capture the real safety indications better, this thesis differentiates the risks in different directions of the roadways, disaggregates different road types, and utilizes GIS to analyze and visualize the spatial relative crash risks in 3-D views according to different temporal scales. Results demonstrate that the approach is effective in spatially smoothing the relative crash risks, eliminating the instability of estimates while maintaining real safety trends. The posterior risk maps show high-risk roadway segments in 3-D views, which is more reader friendly than the conventional 2-D views. The results are also useful for travelers to choose relatively safer routes.