In recent years, the music has become popular due to the evolution of the technology. Various kinds of music around us become complexities and huge. The explosive growth in the music has generated the urgent need for new techniques and tools that can intelligently and automatically transform the music into useful information. Many researches consider the music object as an continuously discrete note in time order. Repeating patterns are some subsequences which appear frequently in the music sequence. The repeating patterns usually can represent the theme of a music object. Moreover, it also can be utilized in music classification. Many methods have been proposed for finding the repeating patterns in music objects, for example, the M2P (Mining Maximum-length Patterns) method. It constructs a directed graph and uses the depth-first search to traverse the graph. It calculates the paths by the string matching algorithm to decide whether they are repeating pattern, and finds out the maximum-length repeating pattern in a music sequence. Although the M2P method is a straightforward method to find out the patterns, it consumes time in creating too many candidate patterns and performing the string matching algorithm. Therefore, in this thesis, we propose the PJ (Position-Join) method to efficiently find out the maximum-length repeating pattern. In the constructing graph step, we find out that we can modify the information in the graph, and avoid to use the string matching algorithm to decide whether a path is repeating pattern. We record the positions of length two repeating patterns in the matrix. While traversing the graph, we calculate the frequency by the information of positions. Moreover, we record the repeated path by the positions. We create terminal edges, and record the information of paths which have been traversed. We dynamically modify the graph by terminal edges. It can avoid to traverse some paths repeatedly in traversing the graph step. From our performance study based on the synthetic data and real music data, we show that our proposed PJ method is more efficient than the M2P method.

General 3D stereo vision is composed of two major phases. In the first phase, an image and its corresponding depth map are generated using stereo matching. In the second phase, depth-based image rendering (DIBR) is employed to generate images of different view angles. Stereo matching, a computation-intensive operation, generates the depth maps from two images captured at two different view positions. In this thesis, we present hardware designs of three different stereo matching methods: pixel-based, window-based, and dynamic programming (DP)-based. Pixel--based and window-based methods belong to the local optimization stereo matching methods while DP, one of the global optimization methods, consists of three main processing steps: matching cost computation, cost aggregation, and back-tracing. Hardware implementation of DP-based stereo matching usually requires large memory space to store the intermediate results, leading to large area cost. In this thesis, we propose a tile-based DP method by partition the original image into smaller tiles so that the processing of each tile requires smaller memory size.

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Depth-Based Image Rendering (DIBR) is a popular method to generate 3D virtual image at different view positions using an image and a depth map. In general, DIBR consists of two major operations: image warping and hole filling. Image warping calculates the disparity from the depth map given some information of viewers and display screen. Hole filling is to calculate the color of pixel locations that do not correspond to any pixels in the original image after image warping. Although there are many different hole filling methods that determine the colors of the blank pixels, some undesirable artifacts are still observed in the synthesized virtual image. In this thesis, we present an approach that examines the geometry information near the region of blank pixels in order to reduce the artifacts near the edges of objects. Experimental results show that the proposed design can generate more natural shape around the edges of objects at the cost of more hardware and computation time.

The image quality will degrade if the misfocusing problem occurs in the imaging system. This paper is aimed to design and analyze a phase mask for mutifocusing problem. Depth of field is the range to get a clear image. As the lens can only gather the light in a fixed range. Image will be more blurred when it is more from this range. In 1995 Dowski and Cathey proposed the wave-front coding to increase the system's depth of field so that the image will less susceptible to blur due to the mutifocusing problem. A treatment with a mask before the lens can extend the depth of field. In this paper, we extend to multi-levels phase mask. The simulation results show that multi-level phase mask has a better performance than the two-level phase mask.

Human behavior analysis is an important challenge in many domains, such as surveillance systems, video content retrieval, human interactive systems, medical diagnosis, etc. With the increasing needs of public safety, intelligent surveillance system becomes an activating issue in computer vision and related research fields. In this thesis we present a method to analyze human behavior in a video sequence with depth information obtained from the depth camera. When interested actions are detected in the scene, the system will trigger alarm information. Contour line and Delaunay triangulation are used to establish human posture model. By traversing the triangulation meshes with the depth first search, we obtain the spanning tree with the depth information, and then construct human posture model with this spanning tree. Posture sequence from video sequence with corresponding posture models can be obtained, and then the posture sequences is clustered into key posture sequence. By querying the key posture sequence, the system can recognize human behavior in real-time and inform users immediately when interested actions detected. Experimental results show that the system is accurate and robust for human behavior recognition.

This research mainly develops a new z-position measurement based on the chromatic aberration effect. An objective-type dark-field illumination scheme is built to produce diascopic chromatic aberration light, and aimed to enhance the signal-to-noise ratio. The xenon lamp is adapted to create white light with continuous spectrum, besides, lens with low Abbe number is needed to extend the degree of chromatic aberration, so lens made of PMMA is as a chromatic aberration component. In the proposed system, the depths of samples in micro-channel is illuminated by the dispersed light and scatter the optical signals, which are captured by a low numerical aperture (N.A.) objective lens. After the simple normalization, the intensity ratio of two selected wavelengths 450 nm (blue light) and 670 nm (red light) from the scattered spectrum becomes a reliable index for the depth information of the detecting objects. By means of establishing the relationship between depth and intensity ratio, every object flowing through diagnosed spot is able to be determined the depth level by cross-referencing the database. By using spectrometer as detector, delicate moving components for light filtering or electrical stage for light scanning can be excluded for high-speed z-position detection. Furthermore, in order to identify the depth level of sample with high flowing rate, avalanche photodiodes are adapted to achieve rapid detection. The experimental results show that the relationship between depth and intensity ratio is a parabola curve, but in this research, the region which tends to behavior linearly is adapted. The proposed system provides a linear detection range of ¡Ó15 £gm for particles with a diameter of 20 £gm. The lens with high Abbe number only obtains ¡Ó10 £gm with linear detection range though, the resolution for size is better than PMMA. The BK7 lens is capable to discriminate the depth change of 2 £gm micro-beads, note that there is no limitation of depth discrimination in this system, because of the measurement is achieved by cross-referencing the linear line. The use of UV-Vis-NIR spectrometer enable this system to analyze the depths of the samples in flow rate 0.5 mm/s. To gain the higher performance, the two avalanche photodiodes are utilized, and the short(CWL=450 nm, ¡Ó20 nm) and long(CWL=650 nm, ¡Ó20 nm) band pass filter are also equipped to represent enhancements of blue and red ray. The effective detection range extends to ¡Ó25 £gm and has high linearity(R square=0.99285) after the optimization of light stop. In high flowing rate detection, this system is able to identify the depth of sample when the flow velocity is 4.167 mm/s, the calculated throughput is 126 particles/s. It also successfully analyzes the depth of flowing human erythrocytes under the flow velocity is 2.778 mm/s, the velocity which the developed system is capable to analyze is about 5-8 folds to the conventional micro-PIV system. With this novel and simple approach, there will be the quantified information from z-direction of flowing body for bio-analysis, and also benefits estimating the performance of micro structure or device in the microfluidic chip, also the analysis of flow field. Except for dynamical detection, this system also be capable to apply in a open and static situation, such as cell or tissue proliferation assay.

Recently, stereo vision has been widely used in many applications, and depth map is important information in stereo vision. In general, depth map can be generated from the disparity using stereo matching based on two input images of different viewing positions. Due to the large computation complexity, software implementation of stereo matching usually cannot achieve real-time computation speed. In this thesis, we propose hardware implementations of stereo matching to speed up the generation of depth map. The proposed design uses a global optimization method, called dynamic programming, to find the disparity based on two input images: left image and right image. It consists of three main processing steps: matching cost computation (M.C.C.), minimum cost accumulation (M.C.A.), and disparity optimization (D.O.). The thesis examines the impact of different pixel operation orders in M.C.C and M.C.A modules on the cost of hardware. In the design of D.O. module, we use two different approaches. One is a Systolic-Like structure with streaming processing, and the other is memory-based design with low hardware cost. The final architecture with pipelining and memory-based D.O. can save a lot of hardware cost and achieve high throughput rate for processing a sequence of image pairs.

The bridge scour depths in cohesive soil have been predicted using the scour equations developed for cohesionless soils due to scarce of studies about cohesive soil. The scour depths predicted by the conventional methods will result in significant errors. For the cost effective design of bridge scour in cohesive soil, the Scour Rate In COhesvie Soil (SRICOS) for the singular circular pier in deep water condition was released in 1999, and has been developed for complex pier and contraction scour. The present study is the part of SRICOS-EFA method to predict the history of contraction scour, and local scours, such as abutment scour and pier scour. The main objective is to develop the prediction methods for the maximum and the uniform contraction scour depth, the maximum pier scour depth and the maximum abutment using flume test results. The equations are basically composed with the difference between the local Froude number and the critical Froude number. Because the scour happens when the shear stress is bigger than the critical shear stress, which is the maximum shear stress the channel bed material can resist from the erosion, and continues until the shear stress becomes equal to the critical shear stress. All results obtained from flume tests for pier scour have been conducted in Texas A&M University from 1997 to 2002 are collected and reanalyzed in this study. Since the original pier scour equation did not include soil properties. The effect of water depth effect, pier spacing, pier shape and flow attack angle for the rectangular pier are studied and correction factors with respect to the circular pier in deep water condition were newly developed in present study. For the abutment scour, a series of flume tests in large scale was performed in the present study. Two types of channel - rectangular channel, and compound channel - were used. The effect of abutment length, shape and alignment of abutment were studied and the correction factors were developed. The patterns of velocity and of scour were compared, and it was found that the maximum local scour occurred where the maximum turbulence was measured. For the contraction scour, the results obtained from a series of flume tests performed in 2002 and a series of flume tests for the abutment scour in the present study are analyzed. The methodologies to predict the maximum contraction scour and the uniform contraction scour in the compound channel was developed. Although all prediction methods developed in the present study are for the cohesive soils, those methods may be applicable to the cohesionless soils because the critical shear stress is included in the methods. All prediction methods were verified by the comparison with the databases obtained from flume test results and field data.

Following the development of new technologies, more and more users can access online mobile content now. Reading news is the most used service in Taiwan. Because of the potential profits of valued-added services in telecommunications, many traditional media are joining this market by providing news content. The author tries to find out the motivations, reasons of partner selection, and the measures of performance of the strategic alliances between telecommunication operators and news content providers by in-depth interviewing managers of telecommunication and media in news mobile content service strategic alliance. This research analyzes the different strategies taken by both parties and evaluates the outcome of strategic alliance. This research indicates that the different managerial culture between alliances would influence the sustainability. Besides, Strategic alliances have the risk of profit-sharing and stray from seeking short-term profit.