Among the various approaches to 3-D imaging, structured light illumination (SLI) is widely spread. SLI employs a pair of digital projector and digital camera such that the correspondences can be found based upon the projecting and capturing of a group of designed light patterns. As an active sensing method, SLI is known for its robustness and high accuracy. In this dissertation, I study the phase shifting method (PSM), which is one of the most employed strategy in SLI. And, three novel approaches in PSM have been proposed in this dissertation. First, by regarding the design of patterns as placing points in an N-dimensional space, I take the phase measuring profilometry (PMP) as an example and propose the edge-pattern strategy which achieves maximum signal to noise ratio (SNR) for the projected patterns. Second, I develop a novel period information embedded pattern strategy for fast, reliable 3-D data acquisition and reconstruction. The proposed period coded phase shifting strategy removes the depth ambiguity associated with traditional phase shifting patterns without reducing phase accuracy or increasing the number of projected patterns. Thus, it can be employed for high accuracy realtime 3-D system. Then, I propose a hybrid approach for high quality 3-D reconstructions with only a small number of illumination patterns by maximizing the use of correspondence information from the phase, texture, and modulation data derived from multi-view, PMP-based, SLI images, without rigorously synchronizing the cameras and projectors and calibrating the device gammas. Experimental results demonstrate the advantages of the proposed novel strategies for 3-D SLI systems.

As a critical step after the discovery of material culture in the field, archaeologists have a need to document these findings with a slew of different physical measurements and photographs from varying perspectives. 3-D imaging is becoming increasingly popular as the primary documenting method to replace the plethora of tests and measurements, but for remote areas 3-D becomes more cumbersome due to physical and environmental constraints. The difficulty of using a 3-D imaging system in such environments is drastically lessened while using the RAHAS technique, since it acquires scans untethered to a computer. The goal of this thesis is to present the RAHAS Structured Light Illumination technique for 3-D image acquisition, and the performance of the RAHAS technique as a measurement tool for documentation of material culture on a field trip to the Rio Platano Biosphere in Honduras.

Fingerprints are the most accurate and widely used biometrics for human identification due to their uniqueness, rapid and easy means of acquisition. Contact based techniques of fingerprint acquisition like traditional ink and live scan methods are not user friendly, reduce capture area and cause deformation of fingerprint features. Also, improper skin conditions and worn friction ridges lead to poor quality fingerprints. A non-contact, high resolution, high speed scanning system has been developed to acquire a 3D scan of a finger using structured light illumination technique. The 3D scanner system consists of three cameras and a projector, with each camera producing a 3D scan of the finger. By merging the 3D scans obtained from the three cameras a nail to nail fingerprint scan is obtained. However, the scans from the cameras do not merge perfectly. The main objective of this thesis is to calibrate the system well such that 3D scans obtained from the three cameras merge or align automatically. This error in merging is reduced by compensating for radial distortion present in the projector of the scanner system. The error in merging after radial distortion correction is then measured using the projector coordinates of the scanner system.

Phase Measuring Profilometry (PMP) is the most robust scanning technique for static 3D data acquisition. To make this technique robust to the target objects which are in motion during the scan interval a novel algorithm called ‘Pattern Interleaving’ is used to get a high density single scan image and making Phase Measuring Profilometry insensitive to ‘z’ motion and prevent motion banding which is predominant in 3D reconstruction when the object is in motion during the scan time

Structured light pattern projection techniques are well known methods of accurately capturing 3-Dimensional information of the target surface. Traditional structured light methods require several different patterns to recover the depth, without ambiguity or albedo sensitivity, and are corrupted by object movement during the projection/capture process. This thesis work presents and discusses a color multiplexed structured light technique for recovering object shape from a single image thus being insensitive to object motion. This method uses single pattern whose RGB channels are each encoded with a unique subpattern. The pattern is projected on to the target and the reflected image is captured using high resolution color digital camera. The image is then separated into individual color channels and analyzed for 3-D depth reconstruction through use of phase decoding and unwrapping algorithms thereby establishing the viability of the color multiplexed single pattern technique. Compared to traditional methods (like PMP, Laser Scan etc) only one image/one-shot measurement is required to obtain the 3-D depth information of the object, requires less expensive hardware and normalizes albedo sensitivity and surface color reflectance variations. A cosine manifold and a flat surface are measured with sufficient accuracy demonstrating the feasibility of a real-time system.

The health and productive output of dairy cows can be closely correlated to individual cow feed intake. Being able to monitor feed intake on a daily basis is beneficial dairy farm management. Each cow can be addressed individually with minimal time required from those working with the animals. This is essential as time management is closely tied to resource management in a dairy operation. Anything that can save time and resources and increase profitability and herd health is a paramount advantage in dairy farming. This study examined the use of machine vision structured light illumination three-dimensional scanning of cow feed to determine the volume and weight of feed in a bin before and after feeding dairy cow. Calibration and control tests were conducted to determine the effectiveness and capability of implementing such a machine vision feed scanning system. Such a system is ideal as it does not obstruct workflow or cow feeding behavior. This is an improvement over existing systems as the system in this research study can be implemented into existing farm operations with minimal effort and costs.

The inclusion of precision dairy farming technologies in dairy operations is an area of increasing research and industry direction. Machine vision based systems are suitable for the dairy environment as they do not inhibit workflow, are capable of continuous operation, and can be fully automated. The research of this dissertation developed and tested 3 machine vision based precision dairy farming technologies tailored to the latest generation of RGB+D cameras. The first system focused on testing various imaging approaches for the potential use of machine vision for automated dairy cow feed intake monitoring. The second system focused on monitoring the gradual change in body condition score (BCS) for 116 cows over a nearly 7 month period. Several proposed automated BCS systems have been previously developed by researchers, but none have monitored the gradual change in BCS for a duration of this magnitude. These gradual changes infer a great deal of beneficial and immediate information on the health condition of every individual cow being monitored. The third system focused on automated dairy cow feature detection using Haar cascade classifiers to detect anatomical features. These features included the tailhead, hips, and rear regions of the cow body. The features chosen were done so in order to aid machine vision applications in determining if and where a cow is present in an image or video frame. Once the cow has been detected, it must then be automatically identified in order to keep the system fully automated, which was also studied in a machine vision based approach in this research as a complimentary aspect to incorporate along with cow detection. Such systems have the potential to catch poor health conditions developing early on, aid in balancing the diet of the individual cow, and help farm management to better facilitate resources, monetary and otherwise, in an appropriate and efficient manner. Several different applications of this research are also discussed along with future directions for research, including the potential for additional automated precision dairy farming technologies, integrating many of these technologies into a unified system, and the use of alternative, potentially more robust machine vision cameras.

Structured Light Illumination is a widely used 3D shape measurement technique in non-contact surface scanning. Multi-pattern based Structured Light Illumination methods reconstruct 3-D surface with high accuracy, but are sensitive to object motion during the pattern projection and the speed of scanning process is relatively long. To reduce this sensitivity, single pattern techniques are developed to achieve a high speed scanning process, such as Composite Pattern (CP) and Modified Composite Pattern (MCP) technique. However, most of single patter techniques have a significant banding artifact and sacrifice the accuracy. We focus on developing SLI techniques can achieve both high speed, high accuracy and have the tolerance to the relative motion. We first present a novel Two-Pattern Full Lateral Resolution (2PFLR) SLI method utilizing an MCP pattern for non-ambiguous phase followed by a single sinusoidal pattern for high accuracy. The surface phase modulates the single sinusoidal pattern which is demodulated using a Quadrature demodulation technique and then unwrapped by the MCP phase result. A single sinusoidal pattern reconstruction inherently has banding error. To effective de-band the surface, we propose Projector Space De-banding algorithm (PSDb). We use projector space because the band error is aligned with the projector coordinates allowing more accurate estimation of the banding error. 2PFLR system only allows the relative motion within the FOV of the scanner, to extend the application of the SLI, we present the research on Relative Motion 3-D scanner which utilize a single pattern technique. The pattern in RM3D system is designed based on MCP but has white space area to capture the surface texture, and a constellation correlation filter method is used to estimate the scanner's trajectory and then align the 3-D surface reconstructed by each frame to a point cloud of the whole object surface.

Structured light illumination (SLI) is the process of projecting a series of light striped patterns such that, when viewed at an angle, a digital camera can reconstruct a 3-D model of a target object's surface. But by relying on a series of time multiplexed patterns, SLI is not typically associated with video applications. For this purpose of acquiring 3-D video, a common SLI technique is to drive the projector/camera pair at very high frame rates such that any object's motion is small over the pattern set. But at these high frame rates, the speed at which the incoming video can be processed becomes an issue. So much so that many video-based SLI systems record camera frames to memory and then apply off-line processing. In order to overcome this processing bottleneck and produce 3-D point clouds in real-time, we present a lookup-table (LUT) based solution that in our experiments, using a 640 by 480 video stream, can generate intermediate phase data at 1063.8 frames per second and full 3-D coordinate point clouds at 228.3 frames per second. These achievements are 25 and 10 times faster than previously reported studies. At the same time, a novel dual-frequency pattern is developed which combines a high-frequency sinusoid component with a unit-frequency sinusoid component, where the high-frequency component is used to generate robust phase information and the unit-frequency component is used to reduce phase unwrapping ambiguities. Finally, we developed a gamma model for SLI, which can correct the non-linear distortion caused by the optical devices. For three-step phase measuring profilometry (PMP), analysis of the root mean squared error of the corrected phase showed a 60х reduction in phase error when the gamma calibration is performed versus 33х reduction without calibration.

Structured Light Illumination (SLI) is the process where spatially varied patterns are projected onto a 3-D surface and based on the distortion by the surface topology, phase information can be calculated and a 3D model constructed. Phase Measuring Profilometry (PMP) is a particular type of SLI that requires three or more patterns temporarily multiplexed. High speed PMP attempts to scan moving objects whose motion is small so as to have little impact on the 3-D model. Given that practically all machine vision cameras and high speed cameras employ a Field Programmable Gate Array (FPGA) interface directly to the image sensors, the opportunity exists to do the processing on camera. This thesis focuses on the design, implementation, testing, and evaluation of a camera-projector system to implement a PMP dual-frequency scheme for 3-D shape measurement on a single FPGA chip. The processor architecture is implemented and tested using the Xilinx Spartan 3 FPGA chip on an Opal Kelly development board. The hardware is described using VHDL and Verilog Hardware Description Languages (HDLs).