<p>A key aspect of color change is altering perceived value or intensity. This dissertation presents a methodology to achieve value change through mechanical means via the deflection of bistable structures. We create the Mechxel, two methods of mechanical pixel-based, reversible color change using 3D printed switchable multistability and bistable switch panels that augment the projected area a viewer perceives which enables the creation of image and character tessellation.</p> <p>Switchable multistability (SMS) arises from the combination of pre-strain and shape memory, allowing us to access multiple elastically programmed shapes at elevated temperatures with fast morphing and low actuation forces, while retaining high stiffness at room temperature. We design and manufacture SMS Mechxels using fused deposition modeling (FDM) 3D printing on the Ultimaker 3D printer in a bilayer layup of polylactic acid (PLA) with a [90/0] print direction while iteratively miniaturizing the physical size to enhance the resolution while also reducing the size of the overall tessellated display. Leveraging SMS properties programmed into each Mechxel, the projected area to a viewer will vary between the unit’s stable states, creating a difference in perceived value of coloration due to changes in area. To ease the tessellation process, we also introduce a tessellation user interface that maps images to their tessellated equivalent to reduce tessellation trial and error. This interface also calculates the number of Mechxels required in their respective states and the final physical size of the display. We then carry out image processing to justify this change in value between stable states and run preliminary optical character recognition.</p> <p>Inspired by mechanical bistable mechanisms, the bistable switch Mechxels utilize changes in a surface’s projected area to a viewer via changes in the angle of a bistable tile using a 5-by-5 grid for character replication and display. Comprising of three main components – two bistable switches, a colored tile and a base, design considerations were made to create an easy to assemble and replaceable 3D printed grid system that could be interacted with by audiences or easily electromechanically actuated. Using pixel-by-pixel comparisons and Sorensen-Dice coefficient, characters using the typeface Silkscreen were documented on these tiled grids yielding high similarity and low error when compared to their digital reference images in various positions and orientations. We also experiment with transitional waves as a promising means of actuation to change the Mechxel between their stable states.</p> <p>The Mechxels considered in this research introduce a new means of purely mechanical color change, character, and image display either leveraging the elastic properties of shape memory polymers (SMPs) or bistable mechanisms. With potential applications in passive morphing architecture, adaptive camouflage, and interactive aesthetic, Mechxels opens the door to limitless design possibilities through a new perspective into color change.</p>

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The aim of this work is to design methods of fingerprint morphing, subsequently to implement the proposed methods and to test their effectiveness by breaking into real verification systems made by Innovatrics and Neurotechnology, two prominent companies in biometrics. Methods for morphing were designed mainly based on the article On the Feasibility of Creating Double-Identity Fingerprints where the part of the preparation of fingerprints on the input was modified and an adjustment of the output was made so that it is able to work with fingerprint images taken under different conditions. Fingerprints created by morphing were recognized as genuine in 41.72 % of cases when compared to the default threshold. The main benefit of this work is the created application for generating fingerprints using morphing and to point out that this method is a\,threat to existing systems used for fingerprint recognition.

The use of CAD models and CFD analysis has become an essential part of fluid flow design. To reduce the time spent determining a design, optimization frameworks have been implemented to automate the process. Mesh morphing has been implemented within these frameworks to further reduce the time needed. While optimization methods have been developed to optimize a fluid flow path, the optimum design needs to be recreated in a CAD model. A method has been developed which eliminates the need to recreate the optimal results in CAD. This is accomplished by using mesh morphing, CAD and CFD together in an optimization framework. The method developed has been implemented with a significant time savings over the use of a traditional meshing optimization framework.

Finite element analysis depends greatly upon a high-quality mesh to be able to provide reasonably accurate answers to engineering problems. Models that need to be analyzed using finite element analysis are becoming increasingly more complex, and correspondingly harder to mesh with good quality. Skew is one quality metric which can cause problems with finite element analyses. This thesis explains how skew is calculated, discusses two common sources of skew: multiply-linked surfaces with interval constraints, and biased edge meshes. Two methods of lessening skew in surface meshes are then presented: the skew control algorithm, and the curve morphing algorithm. These algorithms are discussed in detail, with representative graphics. Examples which demonstrate the skew which arises from the above-mentioned sources are presented. These models are then subjected to the algorithms discussed in the thesis, and a comparison of the skew measure for each example is presented. Finally, areas of possible future work are presented and the possible detrimental effects that the skew control algorithm can exert on the quality metrics of aspect ration and mesh size gradation are discussed.

An enormous amount of the historical record is currently trapped in non-indexed handwritten format. Even after being scanned into images, only a minute fraction of the existing records can be manually transcribed / indexed with reasonable amounts of time and cost. Although progress continues to be made with automatic handwriting recognition (HR), it is not yet good enough to replace manual transcription or indexing. Much of the recent HR work has focused on incremental improvements to methods based on Hidden Markov Models (HMMs) and other similar probabilistic approaches. In this dissertation we present a fundamentally new approach to HR based on 2-D geometric warping of word images. The results of our experimentation indicate that our approach is significantly more accurate than an existing whole-word approach used for word-spotting, and may also be better than HMM-based HR approaches. Since it is a completely new method, we also believe there is potential for improvement and future work that builds on this approach. In addition, we demonstrate that the approach can be used effectively in the related application domain of signature verification and forgery detection.

This dissertation deals with the image-based approach to synthesize a virtual scene using sparse images or a video sequence without the use of 3D models. In our scenario, a real dynamic or static scene is captured by a set of un-calibrated images from different viewpoints. After automatically recovering the geometric transformations between these images, a series of photo-realistic virtual views can be rendered and a virtual environment covered by these several static cameras can be synthesized. This image-based approach has applications in object recognition, object transfer, video synthesis and video compression. In this dissertation, I have contributed to several sub-problems related to image based view synthesis. Before image-based view synthesis can be performed, images need to be segmented into individual objects. Assuming that a scene can approximately be described by multiple planar regions, I have developed a robust and novel approach to automatically extract a set of affine or projective transformations induced by these regions, correctly detect the occlusion pixels over multiple consecutive frames, and accurately segment the scene into several motion layers. First, a number of seed regions using correspondences in two frames are determined, and the seed regions are expanded and outliers are rejected employing the graph cuts method integrated with level set representation. Next, these initial regions are merged into several initial layers according to the motion similarity. Third, the occlusion order constraints on multiple frames are explored, which guarantee that the occlusion area increases with the temporal order in a short period and effectively maintains segmentation consistency over multiple consecutive frames. Then the correct layer segmentation is obtained by using a graph cuts algorithm, and the occlusions between the overlapping layers are explicitly determined. Several experimental results are demonstrated to show that our approach is effective and robust. Recovering the geometrical transformations among images of a scene is a prerequisite step for image-based view synthesis. I have developed a wide baseline matching algorithm to identify the correspondences between two un-calibrated images, and to further determine the geometric relationship between images, such as epipolar geometry or projective transformation. In our approach, a set of salient features, edge-corners, are detected to provide robust and consistent matching primitives. Then, based on the Singular Value Decomposition (SVD) of an affine matrix, we effectively quantize the search space into two independent subspaces for rotation angle and scaling factor, and then we use a two-stage affine matching algorithm to obtain robust matches between these two frames. The experimental results on a number of wide baseline images strongly demonstrate that our matching method outperforms the state-of-art algorithms even under the significant camera motion, illumination variation, occlusion, and self-similarity. Given the wide baseline matches among images I have developed a novel method for Dynamic view morphing. Dynamic view morphing deals with the scenes containing moving objects in presence of camera motion. The objects can be rigid or non-rigid, each of them can move in any orientation or direction. The proposed method can generate a series of continuous and physically accurate intermediate views from only two reference images without any knowledge about 3D. The procedure consists of three steps: segmentation, morphing and post-warping. Given a boundary connection constraint, the source and target scenes are segmented into several layers for morphing. Based on the decomposition of affine transformation between corresponding points, we uniquely determine a physically correct path for post-warping by the least distortion method. I have successfully generalized the dynamic scene synthesis problem from the simple scene with only rotation to the dynamic scene containing non-rigid objects. My method can handle dynamic rigid or non-rigid objects, including complicated objects such as humans. Finally, I have also developed a novel algorithm for tri-view morphing. This is an efficient image-based method to navigate a scene based on only three wide-baseline un-calibrated images without the explicit use of a 3D model. After automatically recovering corresponding points between each pair of images using our wide baseline matching method, an accurate trifocal plane is extracted from the trifocal tensor implied in these three images. Next, employing a trinocular-stereo algorithm and barycentric blending technique, we generate an arbitrary novel view to navigate the scene in a 2D space. Furthermore, after self-calibration of the cameras, a 3D model can also be correctly augmented into this virtual environment synthesized by the tri-view morphing algorithm. We have applied our view morphing framework to several interesting applications: 4D video synthesis, automatic target recognition, multi-view morphing.

View Synthesis is the challenging problem of predicting a new view or pose of an object given an exemplar view or set of views. This thesis presents a novel approach for the problem of view synthesis. The proposed method uses global features rather than local geometry to achieve an effect similar to that of the well known view morphing method . While previous approaches to the view synthesis problem have shown impressive results, they are highly dependent on being able to solve for epipolar geometry and therefore have a very precise correspondence between reference images. In cases where this is not possible such as noisy data, low contrast data, or long wave infrared data an alternative approach is desirable. Here two problems will be considered. The proposed view synthesis method will be used to synthesis new views given a set of reference views. Additionally the algorithm will be extended to synthesis new lighting conditions and thermal signatures. Finally the algorithm will be applied toward enhancing the ATR problem by creating additional training data to increase the likelihood of detection and classification.

Shape morphing in aerospace structures has the potential to reduce noise, improve efficiency, and increase the adaptability of aircraft. Among the many challenges in developing morphing technologies is finding suitable wing skin materials that can be both stiff to support the structural loads, while being elastic and compliant to support this shape morphing an minimize actuation energy. This remains an open challenge, but many possible solutions have been found in smart materials, namely shape memory alloys and polymers. Of these, shape memory polymers have received more attention for wing skins due to their low density and cost, and high elastic limits in excess of 100% strain, but they suffer from generally low overall moduli. Shape memory polymer composites have been considered to address this, typically in the form of particulate/nanoscale reinforcements or by using them as matrix materials in laminate composites. While these can serve to increase the stiffness of the composite, there is still a present need for reinforcement strategies that can also maintain the large changes in stiffness of shape memory polymers. An alternative shape memory composite relies on honeycomb materials with shape memory polymer infills. Previous research has shown that polymer filled honeycombs exhibit greater in-plane moduli greater than the infill or honeycomb alone, but there has been little research focused on understanding this behavior. Moreover, while most engineered cellular structures are comprised of symmetric and periodic cells, cellular structures in nature are commonly spatially varying, asymmetric networks, which have not been considered in these composites. Motivated by these challenges in designing materials for shape morphing, this work seeks to explore the use of shape memory polymer-filled honeycomb composites for use as variable stiffness materials. First, the interaction between infill and the honeycomb, and the relationship between the honeycomb geometry and the effective composite properties is not well understood. This research first investigates the mechanisms of stiffening in these composites through both unit cell finite element models and through experimental characterization. Parametric studies are completed for selected honeycomb geometry design variables, and three key mechanisms of stiffening are identified. Next, these mechanisms are further supported by experimental studies, and comparisons are made showing the limitations of the few existing analytic models. With the knowledge gained from these studies, shape memory polymer infills are considered to create variable stiffness composites. In the first study, sizing design variables are selected to parametric the honeycomb cell geometry, with the designs constrained to be symmetric in-plane. A constrained multiobjective design optimization is completed for two chosen performance objectives, and corresponding local sensitivity studies are completed as well. The results predict that these composites meet and exceed the current bounds of both shape memory polymers and their composites, but also variable stiffness materials in general. A great degree of tailorability is demonstrated, and the model predictions are validated against experimental results from fabricated honeycomb composite samples. Next, generally asymmetric cell geometries are considered by defining shape design variables for the cell geometry. These cells are constrained to be periodic but not symmetric, allowing for the possible benefits of asymmetric to be investigated. Additionally, interconnected and spatially varying multicell unit cells are considered, further allowing for the study of spatially varying cell geometries. Multiobjective optimizations are completed for two unit cell cases, and Pareto fronts are identified. The results are compared to both those from the sizing optimization study and to the current state of the art, and are similarly found to demonstrate high performance and a great degree of tailorability in effective properties. / Doctor of Philosophy / Vehicle shape morphing, the smooth, continuous change of an aircraft's external shape, can greatly improve the efficiency and reduce noise in modern and future vehicles. Among the is challenges in this field is finding suitable skin materials that can be both stiff to support the forces exerted on an aircraft, while being soft and compliant to support this shape morphing. Smart materials, namely shape memory polymers, present many attractive options for this need, but generally need to have a higher stiffness to be suitable for large scale applications. To address this, adding reinforcements to shape memory polymers has been of interest, and current work has largely been focused on using long fiber composites or particulate and nano-reinforcements. As an alternative to these strategies, inspiration can be found in nature where polygon cells are a common means of reinforcement in both plants and animals. Motivated by the current state of the art and the promise of shape morphing structures, this work seeks to investigate cellular structures in the form of hexagonal honeycombs as a means of increasing the stiffness of shape memory polymer infills. This is done by first improving the understanding of more general polymer-filled honeycomb, which exhibit effective stiffnesses greater than the honeycomb or polymer alone. With a working understanding of how the honeycomb stiffens the infill and how the cell geometry influences this behavior, variable modulus infills are next considered. First, sizing design variables (i.e. the lengths and thicknesses of the honeycomb geometry) are selected to describe cell geometries. Design optimization problems are considered and used to estimate the bounds of possible performance for these composites. Relationships between the design variables and the composite performance are investigated, and an improved understanding of these composites is developed. Next, shape design variables are selected to allow for the asymmetry and spatial variation found in natural cellular structures, and similar design optimizations are completed. The results of this work are experimentally validated, and demonstrate that these composites allow for combinations of stiffness and stiffness change that meet and exceed the current state of the art. Furthermore, tailoring the cell geometry allows for an easy means of changing the behavior of the composite. This work represents a great improvement and an important step in overcoming the challenges in developing shape morphing systems.

Traditional and commercial speech synthesizers are incapable of synthesizing speech with proper emotion or prosody. Conveying prosody in artificially synthesized speech is difficult because of extreme variability in human speech. An arbitrary natural language sentence can have different meanings, depending upon the speaker, speaking style, context, and many other factors. Most concatenated speech synthesizers use phonemes, which are phonetic units defined by the International Phonetic Alphabet (IPA). The 50 phonemes in English are standardized and unique units of sound, but not expression. An earlier work proposed the analogy between speech and music ? ?speech is music, music is speech.? The speech data obtained from the master practitioners, who are trained in kinesensic voice, is marked on a five level intonation scale, which is similar to the music scale. From this speech data, 1324 unique expressive units, called expressemes®, are identified. The expressemes consist of melody and rhythm, which, in digital signal processing, is analogous to pitch, duration and energy of the signal. The expressemes have less acoustic and phonetic variability than phonemes, so they better convey the prosody. The goal is to develop a speech synthesizer which exploits the prosodic content of expressemes in order to synthesize expressive speech, with a small speech database. To create a reasonably small database that captures multiple expressions is a challenge because there may not be a complete set of speech segments available to create an emotion. Methods are suggested whereby acoustic mathematical modeling is used to create missing prosodic speech segments from the base prosody unit. New concatenatedormant hybrid speech synthesizer architecture is developed for this purpose. A pitch-synchronous time-varying frequency-warped wavelet transform based prosody manipulation algorithm is developed for transformation between prosodies. A time-varying frequency-warping transform is developed to smoothly concatenate the temporal and spectral parameters of adjacent expressemes to create intelligible speech. Additionally, issues specific to expressive speech synthesis using expressemes are resolved for example, Ergodic Hidden Markov Model based expresseme segmentation, model creation for F0 and segment duration, and target and join cost calculation. The performance of the hybrid synthesizer is measured against a commercially available synthesizer using objective and perceptual evaluations. Subjects consistently rated the hybrid synthesizer better in five different perceptual tests. 70% of speakers rated the hybrid synthesis as more expressive, and 72% preferred it over the commercial synthesizer. The hybrid synthesizer also got a comparable mean opinion score.