Distributed texture-based terrain synthesis

Terrain synthesis is an important field of Computer Graphics that deals with the generation of 3D landscape models for use in virtual environments. The field has evolved to a stage where large and even infinite landscapes can be generated in realtime. However, user control of the generation process is still minimal, as well as the creation of virtual landscapes that mimic real terrain. This thesis investigates the use of texture synthesis techniques on real landscapes to improve realism and the use of sketch-based interfaces to enable intuitive user control

Example based texture synthesis and quantification of texture quality

Textures have been used effectively to create realistic environments for virtual worlds by reproducing the surface appearances. One of the widely-used methods for creating textures is the example based texture synthesis method. In this method of generating a texture of arbitrary size, an input image from the real world is provided. This input image is used for the basis of generating large textures. Various methods based on the underlying pattern of the image have been used to create these textures; however, the problem of finding an algorithm which provides a good output is still an open research issue. Moreover, the process of determining the best of the outputs produced by the existing methods is a subjective one and requires human intervention. No quantification measure exists to do a relative comparison between the outputs. This dissertation addresses both problems using a novel approach. The dissertation also proposes an improved algorithm for image inpainting which yields better results than existing methods. Firstly, this dissertation presents a methodology which uses a HSI (hue, saturation, intensity) color model in conjunction with the hybrid approach to improve the quality of the synthesized texture. Unlike the RGB (red, green, blue) color model, the HSI color model is more intuitive and closer to human perception. The hue, saturation and intensity are better indicators than the three color channels used in the RGB model. They represent the exact way, in which the eye sees color in the real world. Secondly, this dissertation addresses the issue of quantifying the quality of the output textures generated using the various texture synthesis methods. Quantifying the quality of the output generated is an important issue and a novel method using statistical measures and a color autocorrelogram has been proposed. It is a two step method; in the first step a measure of the energy, entropy and similar statistical measures helps determine the consistency of the output texture. In the second step an autocorelogram is used to analyze color images as well and quantify them effectively. Finally, this disseratation prsesents a method for improving image inpainting. In the case of inpainting, small sections of the image missing due to noise or other similar reasons can be reproduced using example based texture synthesis. The region of the image immediately surrounding the missing section is treated as sample input. Inpainting can also be used to alter images by removing large sections of the image and filling the removed section with the image data from the rest of the image. For this, a maximum edge detector method is proposed to determine the correct order of section filling and produces significantly better results

Pixel level data-dependent triangulation with its applications

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Transform domain texture synthesis on surfaces

In the recent past application areas such as virtual reality experiences, digital cinema and computer gamings have resulted in a renewed interest in advanced research topics in computer graphics. Although many research challenges in computer graphics have been met due to worldwide efforts, many more are yet to be met. Two key challenges which still remain open research problems are, the lack of perfect realism in animated/virtually-created objects when represented in graphical format and the need for the transmissiim/storage/exchange of a massive amount of information in between remote locations, when 3D computer generated objects are used in remote visualisations. These challenges call for further research to be focused in the above directions. Though a significant amount of ideas have been proposed by the international research community in their effort to meet the above challenges, the ideas still suffer from excessive complexity related issues resulting in high processing times and their practical inapplicability when bandwidth constraint transmission mediums are used or when the storage space or computational power of the display device is limited. In the proposed work we investigate the appropriate use of geometric representations of 3D structure (e.g. Bezier surface, NURBS, polygons) and multi-resolution, progressive representation of texture on such surfaces. This joint approach to texture synthesis has not been considered before and has significant potential in resolving current challenges in virtual realism, digital cinema and computer gaming industry. The main focus of the novel approaches that are proposed in this thesis is performing photo-realistic texture synthesis on surfaces. We have provided experimental results and detailed analysis to prove that the proposed algorithms allow fast, progressive building of texture on arbitrarily shaped 3D surfaces. In particular we investigate the above ideas in association with Bezier patch representation of 3D objects, an approach which has not been considered so far by any published world wide research effort, yet has flexibility of utmost practical importance. Further we have discussed the novel application domains that can be served by the inclusion of additional functionality within the proposed algorithms.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Image-based procedural texture matching and transformation

In this thesis, we present an approach to finding a procedural representation of a texture to replicate a given texture image which we call image-based procedural texture matching. Procedural representations are frequently used for many aspects of computer generated imagery, however, the ability to use procedural textures is limited by the difficulty inherent in finding a suitable procedural representation to match a desired texture. More importantly, the process of determining an appropriate set of parameters necessary to approximate the sample texture is a difficult task for a graphic artist.The textural characteristics of many real world objects change over time, so we are therefore interested in how textured objects in a graphical animation could also be made to change automatically. We would like this automatic texture transformation to be based on different texture samples in a time-dependant manner. This notion, which is a natural extension of procedural texture matching, involves the creation of a smoothly varying sequence of texture images, while allowing the graphic artist to control various characteristics of the texture sequence.Given a library of procedural textures, our approach uses a perceptually motivated texture similarity measure to identify which procedural textures in the library may produce a suitable match. Our work assumes that at least one procedural texture in the library is capable of approximating the desired texture. Because exhaustive search of all of the parameter combinations for each procedural texture is not computationally feasible, we perform a two-stage search on the candidate procedural textures. First, a global search is performed over pre-computed samples from the given procedural texture to locate promising parameter settings. Secondly, these parameter settings are optimised using a local search method to refine the match to the desired texture.The characteristics of a procedural texture generally do not vary uniformly for uniform parameter changes. That is, in some areas of the parameter domain of a procedural texture (the set of all valid parameter settings for the given procedural texture) small changes may produce large variations in the resulting texture, while in other areas the same changes may produce no variation at all. In this thesis, we present an adaptive random sampling algorithm which captures the texture range (the set of all images a procedural texture can produce) of a procedural texture by maintaining a sampling density which is consistent with the amount of change occurring in that region of the parameter domain.Texture transformations may not always be contained to a single procedural texture, and we therefore describe an approach to finding transitional points from one procedural texture to another. We present an algorithm for finding a path through the texture space formed from combining the texture range of the relevant procedural textures and their transitional points.Several examples of image-based texture matching, and texture transformations are shown. Finally, potential limitations of this work as well as future directions are discussed

A Hybrid Neural Network Architecture for Texture Analysis in Digital Image Processing Applications

A new hybrid neural network model capable of texture analysis in a digital image processing environment is presented in this thesis. This model is constructed from two different types of neural network, self-organisation and back-propagation. Along with a brief resume of digital image processing concepts, an introduction to neural networks is provided. This contains appropriate documentation of the neural networks and test evidence is also presented to highlight the relative strengths and weaknesses of both neural networks. The hybrid neural network is proposed from this evidence along with methods of training and operation. This is supported by practical examples of the system's operation with digital images. Through this process two modes of operation are explored, classification and segmentation of texture content within images. Some common methods of texture analysis are also documented, with spatial grey level dependence matrices being chosen to act as a feature generator for classification by a back-propagation neural network, this provides a benchmark to assess the performance of the hybrid neural network. This takes the form of descriptive comparison, pictorial results, and mathematical analysis when using aerial survey images. Other novel approaches using the hybrid neural network are presented with concluding comments outlining the findings presented within this thesis

SOUND SYNTHESIS WITH CELLULAR AUTOMATA

This thesis reports on new music technology research which investigates the use of cellular automata (CA) for the digital synthesis of dynamic sounds. The research addresses the problem of the sound design limitations of synthesis techniques based on CA. These limitations fundamentally stem from the unpredictable and autonomous nature of these computational models. Therefore, the aim of this thesis is to develop a sound synthesis technique based on CA capable of allowing a sound design process. A critical analysis of previous research in this area will be presented in order to justify that this problem has not been previously solved. Also, it will be discussed why this problem is worthwhile to solve. In order to achieve such aim, a novel approach is proposed which considers the output of CA as digital signals and uses DSP procedures to analyse them. This approach opens a large variety of possibilities for better understanding the self-organization process of CA with a view to identifying not only mapping possibilities for making the synthesis of sounds possible, but also control possibilities which enable a sound design process. As a result of this approach, this thesis presents a technique called Histogram Mapping Synthesis (HMS), which is based on the statistical analysis of CA evolutions by histogram measurements. HMS will be studied with four different automatons, and a considerable number of control mechanisms will be presented. These will show that HMS enables a reasonable sound design process. With these control mechanisms it is possible to design and produce in a predictable and controllable manner a variety of timbres. Some of these timbres are imitations of sounds produced by acoustic means and others are novel. All the sounds obtained present dynamic features and many of them, including some of those that are novel, retain important characteristics of sounds produced by acoustic means