Transporting QoS adaptive flows

Distributed audio and video applications need to adapt to fluctuations in delivered quality of service (QoS). By trading off temporal and spatial quality to available bandwidth, or manipulating the playout time of continuous media in response to variation in delay, audio and video flows can be made to adapt to fluctuating QoS with minimal perceptual distortion. In this paper, we extend our previous work on a QoS Architecture (QoS-A) by populating the QoS management planes of our architecture with a framework for the control and management of multilayer coded flows operating in heterogeneous multimedia networking environments. Two key techniques are proposed: i) an end-to-end rate-shaping scheme which adapts the rate of MPEG-coded flows to the available network resources while minimizing the distortion observed at the receiver; and ii) an adaptive network service, which offers “hard” guarantees to the base layer of multilayer coded flows and “fairness” guarantees to the enhancement layers based on a bandwidth allocation technique called Weighted Fair Sharing.     

A serial combination of connectionist-based classifiers for OCR

In this paper we describe the connectionist-based classification engine of an OCR system. The classification engine is based on a new modular connectionist architecture, where a multilayer perceptron (MLP) acting as a classifier is properly combined with a set of autoassociators – one for each class – trained to copy the input to the output layer. The MLP-based classifier selects a small group of classes with high score, that are afterwards verified by the corresponding autoassociators. The learning samples used to train the classifiers are constructed by means of a synthetic noise generator starting from few grey level characters labeled by the user. We report experimental results for comparing three neural architectures: an MLP-based classifier, an autoassociator-based classifier, and the proposed combined architecture. The experiments show that the proposed architecture exhibits the best performance, without increasing significantly the computational burden. Received March 6, 2000 / Revised July 12, 2000     

Surface approximation to scanned data

A method to approximate scanned data points with a B-spline surface is presented. The data are assumed to be organized in the form of Q _i,j, i=0,…,n; j=0,…,m _i, i.e., in a row-wise fashion. The method produces a C ^{(p-1, q-1)} continuous surface (p and q are the required degrees) that does not deviate from the data by more than a user-specified tolerance. The parametrization of the surface is not affected negatively by the distribution of the points in each row, and it can be influenced by a user-supplied knot vector.     

Rendering optimal solar shadows with plural sunlight depth buffers

We propose a novel method, based on the two-pass Z-buffer algorithm, to calculate shadows with sufficient precision and efficiency for rendering a daytime landscape with solar penumbrae. The special feature of the proposed method is that the shadows can be preserved with a precision superior to that of any visible surface. We use the optimal number of plural shadow buffers to do this; it gives a fairly satisfying trade–off between computation time and quality of shadows.     

Defect detection in textured surfaces using color ring-projection correlation

In this paper, we present a correlation scheme that incorporates a color ring-projection representation for the automatic inspection of defects in textured surfaces. The proposed color ring projection transforms a 2-D color image into a 1-D color pattern as a function of radius. For a search window of width W, data dimensionality is reduced from in the 2-D image to O(W) in the 1-D ring-projection space. The complexity of computing a correlation function is significantly reduced accordingly. Since the color ring-projection representation is invariant to rotation, the proposed method can be applied for both isotropic and oriented textures at arbitrary orientations. Experiments on regular textured surfaces have shown the efficacy of the proposed method. Received: 30 March 2000 / Accepted: 24 July 2001 Correspondence to: D.-M. Tsai (e-mail: iedmtsai@saturn.yzu.edu.tw)     

On Abstraction in Scenarios

Scenarios are ways of representing knowledge. They may take many forms, from films of real events through acted scenes to documented procedures. These forms differ in many ways, including how vivid or abstract they are, how accessible they are as specifications, and how effective they are in helping to elicit requirements. Scenarios, especially as Use Cases, are in use or proposed for many aspects of systems engineering. Understanding of the different forms scenarios may take, and then of the costs and benefits of applying these forms in practice, may be valuable.     

Motion compensated film restoration

Motion picture films are susceptible to local degradations such as dust spots. Other deteriorations are global such as intensity and spatial jitter. It is obvious that motion needs to be compensated for before the detection/correction of such local and dynamic defects. Therefore, we propose a hierarchical motion estimation method ideally suited for high resolution film sequences. This recursive block-based motion estimator relies on an adaptive search strategy and Radon projections to improve processing speed. The localization of dust particles then becomes straightforward. Thus, it is achieved by simple inter-frame differences between the current image and motion compensated successive and preceding frames. However, the detection of spatial and intensity jitter requires a specific process taking advantage of the high temporal correlation in the image sequence. In this paper, we present our motion compensation-based algorithms for removing dust spots, spatial and intensity jitter in degraded motion pictures. Experimental results are presented showing the usefulness of our motion estimator for film restoration at reasonable computational costs. Received: 9 July 2000 / Accepted: 13 January 2002 Correspondence to:S. Boukir     

Appearance-based visual learning and object recognition with illumination invariance

This paper describes a method for recognizing partially occluded objects under different levels of illumination brightness by using the eigenspace analysis. In our previous work, we developed the “eigenwindow” method to recognize the partially occluded objects in an assembly task, and demonstrated with sufficient high performance for the industrial use that the method works successfully for multiple objects with specularity under constant illumination. In this paper, we modify the eigenwindow method for recognizing objects under different illumination conditions, as is sometimes the case in manufacturing environments, by using additional color information. In the proposed method, a measured color in the RGB color space is transformed into one in the HSV color space. Then, the hue of the measured color, which is invariant to change in illumination brightness and direction, is used for recognizing multiple objects under different illumination conditions. The proposed method was applied to real images of multiple objects under various illumination conditions, and the objects were recognized and localized successfully.     

Image retrieval using efficient local-area matching

We present an efficient and accurate method for retrieving images based on color similarity with a given query image or histogram. The method matches the query against parts of the image using histogram intersection. Efficient searching for the best matching subimage is done by pruning the set of subimages using upper bound estimates. The method is fast, has high precision and recall and also allows queries based on the positions of one or more objects in the database image. Experimental results showing the efficiency of the proposed search method, and high precision and recall of retrieval are presented. Received: 20 January 1997 / Accepted: 5 January 1998     

Using vanishing points for camera calibration and coarse 3D reconstruction from a single image

In this paper, we show how to calibrate a camera and to recover the geometry and the photometry (textures) of objects from a single image. The aim of this work is to make it possible walkthrough and augment reality in a 3D model reconstructed from a single image. The calibration step does not need any calibration target and makes only four assumptions: (1) the single image contains at least two vanishing points, (2) the length (in 3D space) of one line segment (for determining the translation vector) in the image is known, (3) the principle point is the center of the image, and (4) the aspect ratio is fixed by the user. Each vanishing point is determined from a set of parallel lines. These vanishing points help determine a 3D world coordinate system R _o. After having computed the focal length, the rotation matrix and the translation vector are evaluated in turn for describing the rigid motion between R _o and the camera coordinate system R _c. Next, the reconstruction step consists in placing, rotating, scaling, and translating a rectangular 3D box that must fit at best with the potential objects within the scene as seen through the single image. With each face of a rectangular box, a texture that may contain holes due to invisible parts of certain objects is assigned. We show how the textures are extracted and how these holes are located and filled. Our method has been applied to various real images (pictures scanned from books, photographs) and synthetic images.     

The Design of Human–Machine Interface for Accident Support in Nuclear Power Plants

As feedback from Three Mile Island No. 2, a large amount of human–machine interface (HMI) design has been proposed to support operators during accidents by presenting information on plant status, some of which is implemented in commercial nuclear power plants (NPPs). However, it has not yet been discussed what role HMI should play under conditions where operators must take action as instructed under emergency operating procedure. Regarding this principal issue, an HMI design is proposed together with specific screen images. The advantage of this design is based on the involvement of an ex-operator in NPP in this paper. The participation of users in the design of HMI has been rare. Accordingly the proposed HMI is comprehensive for average operators and is expected to be acceptable for future implementation in commercial NPPs. The effectiveness of the proposed HMI has been examined in a small experiment.     

An efficient animation of wrinkled cloth with approximate implicit integration

This paper presents an efficient method for creating the animation of flexible objects. The mass-spring model was used to represent flexible objects. The easiest approach to creating animation with the mass-spring model is the explicit Euler method, but the method has a serious weakness in that it suffers from an instability problem. The implicit integration method is a possible solution, but a critical flaw of the implicit method is that it involves a large linear system. This paper presents an approximate implicit method for the mass-spring model. The proposed technique updates with stability the state of n mass points in O(n) time when the number of total springs is O(n). In order to increase the efficiency of simulation or reduce the numerical errors of the proposed approximate implicit method, the number of mass points must be as small as possible. However, coarse discretization with a small number of mass points generates an unrealistic appearance for a cloth model. By introducing a wrinkled cubic spline curve, we propose a new technique that generates realistic details of the cloth model, even though a small number of mass points are used for simulation.     

Maximum mutual information training for an online neural predictive handwritten word recognition system

In this paper, we present a hybrid online handwriting recognition system based on hidden Markov models (HMMs). It is devoted to word recognition using large vocabularies. An adaptive segmentation of words into letters is integrated with recognition, and is at the heart of the training phase. A word-model is a left-right HMM in which each state is a predictive multilayer perceptron that performs local regression on the drawing (i.e., the written word) relying on a context of observations. A discriminative training paradigm related to maximum mutual information is used, and its potential is shown on a database of 9,781 words. Received June 19, 2000 / Revised October 16, 2000     

Analysis and verification of real-time systems using quantitative symbolic algorithms

The task of checking if a computer system satisfies its timing specifications is extremely important. These systems are often used in critical applications where failure to meet a deadline can have serious or even fatal consequences. This paper presents an efficient method for performing this verification task. In the proposed method a real-time system is modeled by a state-transition graph represented by binary decision diagrams. Efficient symbolic algorithms exhaustively explore the state space to determine whether the system satisfies a given specification. In addition, our approach computes quantitative timing information such as minimum and maximum time delays between given events. These results provide insight into the behavior of the system and assist in the determination of its temporal correctness. The technique evaluates how well the system works or how seriously it fails, as opposed to only whether it works or not. Based on these techniques a verification tool called Verus has been constructed. It has been used in the verification of several industrial real-time systems such as the robotics system described below. This demonstrates that the method proposed is efficient enough to be used in real-world designs. The examples verified show how the information produced can assist in designing more efficient and reliable real-time systems.     

A hybrid approach for stereo disparity computation

An alternative, hybrid approach for disparity estimation, based on the phase difference technique, is presented. The proposed technique combines the robustness of the matching method with the sub-pixel accuracy of the phase difference approach. A matching between the phases of the left and right signals is introduced in order to allow the phase difference method to work in a reduced disparity range. In this framework, a new criterion to detect signal singularities is proposed. The presented test cases show that the performance of the proposed technique in terms of accuracy and density of the disparity estimates has greatly improved. Received: 24 June 1997 / Accepted: 15 September 1998     

Design and analysis of a video-on-demand server

The availability of high-speed networks, fast computers and improved storage technology is stimulating interest in the development of video on-demand services that provide facilities similar to a video cassette player (VCP). In this paper, we present a design of a video-on-demand (VOD) server, capable of supporting a large number of video requests with complete functionality of a remote control (as used in VCPs), for each request. In the proposed design, we have used an interleaved storage method with constrained allocation of video and audio blocks on the disk to provide continuous retrieval. Our storage scheme interleaves a movie with itself (while satisfying the constraints on video and audio block allocation. This approach minimizes the starting delay and the buffer requirement at the user end, while ensuring a jitter-free display for every request. In order to minimize the starting delay and to support more non-concurrent requests, we have proposed the use of multiple disks for the same movie. Since a disk needs to hold only one movie, an array of inexpensive disks can be used, which reduces the overall cost of the proposed system. A scheme supported by our disk storage method to provide all the functions of a remote control such as “fast-forwarding”, “rewinding” (with play “on” or “off”), “pause” and “play” has also been discussed. This scheme handles a user request independent of others and satisfies it without degrading the quality of service to other users. The server design presented in this paper achieves the multiple goals of high disk utilization, global buffer optimization, cost-effectiveness and high-quality service to the users.     

Stop word location and identification for adaptive text recognition

Abstract. We propose a new adaptive strategy for text recognition that attempts to derive knowledge about the dominant font on a given page. The strategy uses a linguistic observation that over half of all words in a typical English passage are contained in a small set of less than 150 stop words. A small dictionary of such words is compiled from the Brown corpus. An arbitrary text page first goes through layout analysis that produces word segmentation. A fast procedure is then applied to locate the most likely candidates for those words, using only widths of the word images. The identity of each word is determined using a word shape classifier. Using the word images together with their identities, character prototypes can be extracted using a previously proposed method. We describe experiments using simulated and real images. In an experiment using 400 real page images, we show that on average, eight distinct characters can be learned from each page, and the method is successful on 90% of all the pages. These can serve as useful seeds to bootstrap font learning. Received October 8, 1999 / Revised March 29, 2000     

Delay-jitter control in multimedia applications

The growing needs of multimedia communications are leading to new developments in providing real-time communication with guarantees. Several extensions have been proposed for different layers of the Open Systems Interconnection Reference Model to accomodate these needs. In this paper, we study methods for guaranteeing delay jitter bounds for high-speed networks in the network and application layers of this model. The method proposed for the network layer provides distributed jitter control. The method proposed for the application layer allows the destination application to control delay jitter. We use a simulation to compare the effects on delay jitter in each method for various scenarios, such as constant bit rate, cross traffic, and bursty data. In addition, the buffer space requirements for accommodating real-time channels are monitored at each node in the network.     

Fractal analysis of tumor in brain MR images

Abstract. The purpose of this study is to discuss existing fractal-based algorithms and propose novel improvements of these algorithms to identify tumors in brain magnetic-response (MR) images. Considerable research has been pursued on fractal geometry in various aspects of image analysis and pattern recognition. Magnetic-resonance images typically have a degree of noise and randomness associated with the natural random nature of structure. Thus, fractal analysis is appropriate for MR image analysis. For tumor detection, we describe existing fractal-based techniques and propose three modified algorithms using fractal analysis models. For each new method, the brain MR images are divided into a number of pieces. The first method involves thresholding the pixel intensity values; hence, we call the technique piecewise-threshold-box-counting (PTBC) method. For the subsequent methods, the intensity is treated as the third dimension. We implement the improved piecewise-modified-box-counting (PMBC) and piecewise-triangular-prism-surface-area (PTPSA) methods, respectively. With the PTBC method, we find the differences in intensity histogram and fractal dimension between normal and tumor images. Using the PMBC and PTPSA methods, we may detect and locate the tumor in the brain MR images more accurately. Thus, the novel techniques proposed herein offer satisfactory tumor identification. Received: 13 October 2001 / Accepted: 28 May 2002 Correspondence to: K.M. Iftekharuddin     

Making Workflow Change Acceptable

Virtual professional communities are supported by network information systems composed from standard Internet tools. To satisfy the interests of all community members, a user-driven approach to requirements engineering is proposed that produces not only meaningful but also acceptable specifications. This approach is especially suited for workflow systems that support partially structured, evolving work processes. To ensure the acceptability, social norms must guide the specification process. The RENISYS specification method is introduced, which facilitates this process using composition norms as formal representations of social norms. Conceptual graph theory is used to represent four categories of knowledge definitions: type definitions, state definitions, action norms and composition norms. It is shown how the composition norms guide the legitimate user-driven specification process by analysing a case on the development of an electronic law journal.