An empirically derived system for high-speed shadow rendering

Shadows have captivated humanity since the dawn of time; with the current age being no exception – shadows are core to realism and ambience, be it to invoke a classic Baroque interplay of lights, darks and colours as the case in Rembrandt van Rijn’s Militia Company of Captain Frans Banning Cocq or to create a sense of mystery as found in film noir and expressionist cinematography. Shadows, in this traditional sense, are regions of blocked light – the combined effect of placing an object between a light source and surface. This dissertation focuses on real-time shadow generation as a subset of 3D computer graphics. Its main focus is the critical analysis of numerous real-time shadow rendering algorithms and the construction of an empirically derived system for the high-speed rendering of shadows. This critical analysis allows us to assess the relationship between shadow rendering quality and performance. It also allows for the isolation of key algorithmic weaknesses and possible bottleneck areas. Focusing on these bottleneck areas, we investigate several possibilities of improving the performance and quality of shadow rendering; both on a hardware and software level. Primary performance benefits are seen through effective culling, clipping, the use of hardware extensions and by managing the polygonal complexity and silhouette detection of shadow casting meshes. Additional performance gains are achieved by combining the depth-fail stencil shadow volume algorithm with dynamic spatial subdivision. Using this performance data gathered during the analysis of various shadow rendering algorithms, we are able to define a fuzzy logic-based expert system to control the real-time selection of shadow rendering algorithms based on environmental conditions. This system ensures the following: nearby shadows are always of high-quality, distant shadows are, under certain conditions, rendered at a lower quality and the frames per second rendering performance is always maximised.Dissertation (MSc)--University of Pretoria, 2009.Computer Scienceunrestricte

Assessment of paint appearance quality in the automotive industry

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.In the modem automotive industry, more and more manufacturers recognise that vehicle paint appearance makes an important contribution to customer satisfaction. Attractive appearance has become one of the important factors for customers in making a decision to purchase a car. Objective measurement of the quality of autobody paint appearance, as perceived by the customer, in a repeatable, reproducible, continuous scale manner is an important requirement for improving the paint appearance. It can provide car manufacturers a standard reference to evaluate the quality of the paint appearance. This thesis mainly deals with the measurement of paint appearance quality in the automotive industry by investigating, identifying and developing measurement methods in this area. First of all, the 'state of the art' in the area of paint appearance measurement was presented, which summarised the concept of appearance, models, attributes and definitions. To further identify the parameters and instruments used in the automotive industry, a round robin test was launched to perform visual assessment and instrument measurements on a set of panels in some European car manufacturers. A summary of the correlation found between measurable parameters and visual assessment provided the basis of the further work. Based on the literature survey and round robin test results, the next work is mainly concentrated on the two most important parameters, 'orange peel' and 'metal texture effect', how to separate and evaluate them. Digital signal processing technique, FFT and Filtering, have been employed to separate them and a set of measures have been provided for evaluation. At the same time, the technique for texture pattern recognition was introduced to evaluate the texture effect when a fine texture comparison was needed. A set of computable textural parameters based on grey-tone spatial-dependence matrices gives good correlation directly corresponding to visual perception. To resolve the overall appearance modelling problem, two novel and more powerful modelling tools, artificial neural networks and fuzzy logic, are introduced to model the overall appearance. The test results showed that both of them are able to reflect the correlation between overall appearance and the major parameters measured from a painted surface. Finally, an integrated measurement system, 'Smart Appearance', was developed using the image processing techniques and the artificial neural network model. The implement results show that this system can measure the major attributes of paint appearance and provide an overall appearance index corresponding to human visual perception. This system is helpful to product quality control on car body paint. It also could be used on the paint production line for dynamic measurement.European Union BRITE EURAM Projec

Workshop on Fuzzy Control Systems and Space Station Applications

The Workshop on Fuzzy Control Systems and Space Station Applications was held on 14-15 Nov. 1990. The workshop was co-sponsored by McDonnell Douglas Space Systems Company and NASA Ames Research Center. Proceedings of the workshop are presented

Character Recognition

Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field

Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 2

Papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake, held 1-3 Jun. 1992 at the Lyndon B. Johnson Space Center in Houston, Texas are included. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making

Methodology for predicting and/or compensating the behavior of optical frequency comb

RESUMEN: Optical frequency comb spectrum can change its behavior due to temperature fluctuations, normal dispersion, and mechanical vibrations. Such limitations can affect the peak power and wavelength separation of comb lines. In the propagation through single−mode fiber, the linear and non−linear phenomena can modify spectral shape, phase shifts and flatness of spectrum. To find a strategy of compensation, the PhD thesis is focused on a prediction methodology based on fuzzy cellular automata, intuitionistic fuzzy sets and fuzzy entropy measures. The research work proposes a predictor called intuitionistic fuzzy cellular automata based on mean vector and a validation measure called general intuitionistic fuzzy entropy based on adequacy and non−adequacy. In the accomplished experiments, the method was used in three experiments: mode−locked lasers, cascaded intensity modulators−Mach Zehnder modulators, and microresonator ring. The obtained results showed that the power and phase distortions were reduced by using a pulse shaper, where the method was programmed. In addition, the stability and/or instability of spectrum were found for the microresonator ring

Text Segmentation in Web Images Using Colour Perception and Topological Features

The research presented in this thesis addresses the problem of Text Segmentation in Web images. Text is routinely created in image form (headers, banners etc.) on Web pages, as an attempt to overcome the stylistic limitations of HTML. This text however, has a potentially high semantic value in terms of indexing and searching for the corresponding Web pages. As current search engine technology does not allow for text extraction and recognition in images, the text in image form is ignored. Moreover, it is desirable to obtain a uniform representation of all visible text of a Web page (for applications such as voice browsing or automated content analysis). This thesis presents two methods for text segmentation in Web images using colour perception and topological features. The nature of Web images and the implicit problems to text segmentation are described, and a study is performed to assess the magnitude of the problem and establish the need for automated text segmentation methods. Two segmentation methods are subsequently presented: the Split-and-Merge segmentation method and the Fuzzy segmentation method. Although approached in a distinctly different way in each method, the safe assumption that a human being should be able to read the text in any given Web Image is the foundation of both methods’ reasoning. This anthropocentric character of the methods along with the use of topological features of connected components, comprise the underlying working principles of the methods. An approach for classifying the connected components resulting from the segmentation methods as either characters or parts of the background is also presented

Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 2

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Texas, Houston. Topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making

Fuzzy Logic

The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems