17111860
Texture segmentation using directional empirical mode decomposition
In this paper the technique of directional empirical mode decomposition (DEMD) and its application to texture segmentation are presented. Empirical mode decomposition (EMD) decomposes signals by sifting and then analyzes the instantaneous frequency of the obtained components called intrinsic mode functions (IMF). As a new form of extending 1D EMD to the 2D case, DEMD considers the directional frequency and envelope at each point. One type of 2D Hilbert transform is introduced to compute the analytical functions for the frequency and envelope. The technique of selecting directions for DEMD based on texture's Wold theory is also presented. Experimental results indicate the effectiveness of the method for texture segmentation.
6770113
Image magnification method using joint diffusion
In this paper a new algorithm for image magnification is presented. Because linear magnification/interpolation techniques diminish the contrast and produce sawtooth effects, in recent years, many nonlinear interpolation methods, especially nonlinear diffusion based approaches, have been proposed to solve these problems. Two recently proposed techniques for interpolation by diffusion, forward and backward diffusion (FAB) and level-set reconstruction (LSR), cannot enhance the contrast and smooth edges simultaneously. In this article, a novel Partial Differential Equations (PDE) based approach is presented. The contributions of the paper include: firstly, a unified form of diffusion joining FAB and LSR is constructed to have all of their virtues; secondly, to eliminate artifacts of the joint diffusion, soft constraint takes the place of hard constraint presented by LSR; thirdly, the determination of joint coefficients, criterion for stopping time and color image processing are also discussed. The results demonstrate that the method is visually and quantitatively better than Bicubic, FAB and LSR.
62682777
Texture classification through directional empirical mode decomposition
This work presents a method for texture classification through directional empirical mode decomposition (DEMD). Although there have been many filtering based techniques proposed for texture retrieval, problems of non-adaptivity and redundancy are still hard to solve simultaneously. As a technique being introduced into signal processing, empirical mode decomposition (EMD) is an adaptive and approximately orthogonal filtering process. To apply EMD to texture classification, we propose a new method of extending 1-D EMD to 2-D case called DEMD. The approach adaptively decomposes images into local narrow band ingredients-intrinsic mode functions (IMFs) and extracts their features including frequency and envelopes. To improve its classification ability the fractal dimensions of the IMFs are also considered. Decomposition of several directions is computed for rotation invariance. Experiments for textures in Brodatz set and USC database indicate the effectiveness of our technique.
17193716
Detecting news reporting using audio/visual information
This paper proposes an integrated approach to discriminate news reporting from everything else in broadcast news data based on both audio and visual information. The separation of news reporting segments from others not only can provide useful indices for video streams but also serves as a pre-processing step for tasks such as speaker identification and speech recognition so that only speech segments are passed on for further processing. A set of audio and visual features are adopted that aim at capturing the intrinsic properties of the underlying classes. Four types of classifiers (threshold fuzzy, Gaussian Mixture Model based, and Support Vector Machine) are tested. Some of the experimental results are presented and discussed in the paper.
7545798
Verification of fault tolerance and real time
A transformational method is given for specifying and verifying fault-tolerant, real-time programs. Such a program needs to be provably correct according to both its functional and real-time requirements, despite the possible occurrence of system failures. The paper demonstrates that a suitably expressive logic for real-time systems makes it possible to naturally model the state changes caused by system failures and determine their effect on the functional and real-time properties of executions.
11497838
On organizing and accessing geospatial and georeferenced Web resources using the G-Portal system
In order to organise and manage geospatial and georeferenced information on the Web making them convenient for searching and browsing, a digital portal known as G-Portal has been designed and implemented. Compared to other digital libraries, G-Portal is unique for several of its features. It maintains metadata resources in XML with flexible resource schemas. Logical groupings of metadata resources as projects and layers are possible to allow the entire metadata collection to be partitioned differently for users with different information needs. These metadata resources can be displayed in both the classification-based and map-based interfaces provided by G-Portal. G-Portal further incorporates both a query module and an annotation module for users to search metadata and to create additional knowledge for sharing respectively. G-Portal also includes a resource classification module that categorizes resources into one or more hierarchical category trees based on user-defined classification schemas. This paper gives an overview of the G-Portal design and implementation. The portal features will be illustrated using a collection of high school geography examination-related resources.
35062719
Vision Guided Circumnavigating Autonomous Robots
We present a system for vision guided autonomous circumnavigation, allowing a mobile robot to navigate safely around objects of arbitrary pose, and avoid obstacles. The system performs model-based object recognition from an intensity image. By enabling robots to recognize and navigate with respect to particular objects, this system empowers robots to perform deterministic actions on specific objects, rather than general exploration and navigation as emphasized in much of the current literature. This paper describes a fully integrated system, and, in particular, introduces canonical-views. Further, we derive a direct algebraic method for finding object pose and position for the four-dimensional case of a ground-based robot with uncalibrated vertical movement of its camera. Vision for mobile robots can be treated as a very different problem to traditional computer vision, as mobile robots have a characteristic perspective, and there is a causal relation between robot actions and view changes. Canonical-views are a novel, active object representation designed specifically to take advantage of the constraints of the robot navigation problem to allow efficient recognition and navigation.
3758350
An Analytical Approach to the Performance Evaluation of Master-Slave Computational Models
Abstract Many stochastic models and analysis techniques have been proposed in the literature during the last two decades for the performance evaluation of parallel and distributed systems. However, few of them are directly applicable to practical systems which are generally too complex. In this paper, we analyze performances of the master–slave computational model, one of the most commonly used models in parallel and distributed computations. We propose a hybrid analytical approach by using techniques from the theories of both stochastic task graphs and queueing networks. We apply this method to the analysis of a computational chemistry application running on a Transputer based system. The proposed method turns out to be not only very efficient in time for large systems but also very accurate compared to measuring.