The developing of multimedia to make the video data to increase very quickly.So how to acquire the data that we want in a short time is a more important topic. Shot change detection is the first step for latter operation like classification and annotations. There are two type of shot change, one is abrupt shot change and the other one is gradual transition. Dissolve is the one of gradual transition that often seen but hard to detection, so in the paper would to propose a robust method to solve this problem. In this paper we use fractal orthonormal basis for our feature to compare frames in the video to the first frame of video, and use the quantification between those frames to draw a graph. By analyzing the graph and the characteristic of dissolve in the graph we can locate the approximately the start frame and the end frame of the dissolve. But by the action of video camera or motion of object in frame we may obtained the inaccurate start frame or end frame of the dissolve. So we need to refine the more accurate start and end frame of the dissolve, and we will explain about this in Chapter 3-4

Digital multimedia can be distributed via the internet efficiently with superior compression technologies. The chance of distributing digital intellectual properties, such as image, music, films, and software, being large-scale unauthorized copied and distributed are much increasing one possible and practical solution for the copyright protection is information hiding technology. Information hiding technology embeds a special data into multimedia data for copyright protection. However, the embedded data may be damaged by malicious attacks or common signal processing. In this thesis, an information hiding technique based on Fractal Orthonormal Basis is proposed. First, the original image is divided into NxN Range blocks, each range block is substituted by several Domain blocks (Fractal Orthonormal Basis), then the watermark information is embedded into the coefficients of the fractal orthonormal basis. Besides, our technique will be compare with the other two watermarking algorithm (using DCT and DWT). After the attacks of cropping, down-scaling, median filter, smoothing, noise, JPEG, SPIHT and EZW compression, the Fractal Orthonormal Basis watermarking technique shows better result of capacity, transparency and robustness. In addition, we only store parts of compression fractal codes and the permutation seed, and these can be the secret key for the security.

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I give an overview of the basic theory of Hilbert spaces necessary to understand the convergence of the Fourier series for square integrable functions. I state the necessary theorems and definitions to understand the formulations of the problem in a Hilbert space framework, and then I give some applications of the theory along the way.

The objective of the present work is to propose a novel method to extract a stable feature set representative of image content. Each image is represented by a linear combination of fractal orthonormal basis vectors. The mapping coefficients of an image projected onto each orthonormal basis constitute the feature vector. The set of orthonormal basis vectors are generated by utilizing fractal iterative function through target and domain blocks mapping. The distance measure remains consistent, i.e., isometric embedded, between any image pairs before and after the projection onto orthonormal axes. Not only similar images generate points close to each other in the feature space, but also dissimilar ones produce feature points far apart. The above statements are logically equivalent to that distant feature points are guaranteed to map to images with dissimilar contents, while close feature points correspond to similar images. In this paper, we adapt the Multiple Instance Learning paradigm using the Diverse Density algorithm as a way of modeling the ambiguity in images in order to learning concepts used to classify images. A user labels an image as positive if the image contains the concepts, as negative if the image far from the concepts. Each example image is a bag of blocks where only the bag is labeled. The User selects positive and negative image examples to train the concepts in feature space. From a small collection of positive and negative examples, the system learns the concepts using them to retrieve images that contain the concepts from database. Each concept having similar blocks becomes the group in each image. According groups¡¦ location distribution, variation and spatial relations computes positive examples and database images similarity.

During the Digital Period, the more people using these digital video. When there are more and more users and amount of video data, the management of video data becomes a significant dimension during development. Therefore, there are more and more studying of accomplishing video database system, which provide users to search and get them. In this paper, a novel method for Video Scene Change Detection and video database retrieval is proposed. Uses Fractal orthonormal bases to guarantee the similar index has the similar image the characteristic union support vector clustering, splits a video into a sequence of shots, extracts a few representative frames(key-frames) to take the video database index from each shot. When image search compared to, according to MIL to pick up the characteristic, which images pursues the video database to have the similar characteristic, computation similar, makes the place output according to this.

Eight roughness configurations in Clemson boundary layer wind tunnel are presented. For these configurations, flow parameters such as turbulent intensities, integral length scales, large- and small- scale turbulence, and spectra of velocity components of the wind are obtained and studied to the simulated turbulence. At the same time, new analyzing tools, orthogonal wavelet techniques, are applied to provide additional information in time domain. This makes it possible to study the intermittency event, one important characteristic associated with pressure peak activities in turbulence. Three parameters, scale energy, intermittency factor and intermittency energy are defined. Variation of these quantities as a result of different configuration is discussed. Finally, the corresponding variations in measured pressure peaks in relation with the variations of configuration as well as with the intermittency parameters are investigated. The work here is of important significance for future wind tunnel and field data comparison, and this could help to find the best simulation among all configurations. / Master of Science

In this dissertation, the classical problems of testing goodness-of-fit of uniformity and parametric families are reconsidered. A new omnibus test for these problems is proposed and investigated. The new test statistics are a combination of Bayesian and score test ideas. More precisely, singletons that contain only one more parameter than the null describing departures from the null model are introduced. A Laplace approximation to the posterior probability of the null hypothesis is used, leading to test statistics that are weighted sums of exponentiated squared Fourier coefficients. The weights depend on prior probabilities and the Fourier coefficients are estimated based on score tests. Exponentiation of Fourier components leads to tests that can be exceptionally powerful against high frequency alternatives. Comprehensive simulations show that the new tests have good power against high frequency alternatives and perform comparably to some other well-known omnibus tests at low frequency alternatives. Asymptotic distributions of the proposed test are derived under null and alternative hypotheses. An application of the proposed test to an interesting real problem is also presented.

The exact D-optimal design problems for regression models has been in-vestigated in many literatures. Huang (1987) and Gaffke (1987) provided a sufficient condition for the minimum sample size for an certain set of candidate designs to be exact D-optimal for polynomial regression models on a compact interval. In this work we consider a mixture experiment with q nonnegative components, where the proportions of components are sub- ject to the simplex restriction $sum_{i=1}^q x_i =1$, $x_i ¡Ù 0$. The exact D-optimal designs for mixture experiments for Scheffe¡¦s quadratic models are investigated. Based on results in Kiefer (1961) results about the exact D-optimal designs for mixture models with two or three ingredients are provided and numerical verifications for models with ingredients between four and nine are presented.

From the beginning of the study of spaces in functional analysis, bases have been an indispensable tool for operating with vectors and functions over a concrete space. Bases can be organized by types, depending on their properties. This thesis is intended to give an overview of some bases and their relations. We study Hamel basis, Schauder basis and Orthonormal basis; we give some properties and compare them in different spaces, explaining the results. For example, an infinite dimensional Hilbert space will never have a basis which is a Schauder basis and a Hamel basis at the same time, but if this space is separable it has an orthonormal basis, which is also a Schauder basis. The project deals mainly with Banach spaces, but we also talk about the case when the space is a pre Hilbert space.