Department of Computer Science and Information Systems

Permanent URI for this collectionhttp://localhost:4000/handle/123456789/1928

Browse

Start date: 1993End date: 1999

Search Results

Now showing 1 - 10 of 13
  • No Thumbnail Available
    Item
    Efficient algorithms for delay-bounded minimum cost path problem in communication networks
    (IEEE, 1998) Narang, Nishit
    As the amount of data transmitted over a network increases and high bandwidth applications requiring point to multipoint communications like videoconferencing, distributed database management or cooperative work become widespread, it becomes very important to optimize network resources. One such optimization is multicast tree generation. The problem of generating a minimum cost multicast tree given the network topology and costs associated with the connecting links can be modelled as a Steiner tree problem which is NP-complete. Much work has been done in the direction of obtaining near-optimal multicast trees when the objective is only to minimize the cost. However, many real time applications such as videoconferencing require that data be sent within prespecified delay limits in order to avoid problems such as anachronism and lack of synchronization. We deal with the delay-bounded cost-optimal multicast tree (DBCPAT) generation problem. Specifically, we discuss a closely related problem which is to find a delay-bounded cost-optimal path (DBCP) between a specified source and destination node. Such a path can be used as a starting point to solve the DBCMT. We present an exact solution to the DBCP which is based on the branch-and-bound paradigm. We also propose a heuristic technique to solve the DBCP using the principle of evolutionary computing. The results obtained using the two techniques are compared for several large networks.
  • No Thumbnail Available
    Item
    Efficient Algorithms for Delay-bounded Multicast Tree Generation for Multimedia Applications
    (Springer, 1999) Narang, Nishit
    Given a network topology and costs associated with the links, the problem of generating a minimum cost multicast tree can be modelled as a Steiner tree problem. However, many real time applications such as video-conferencing require that data be sent within prespecified delay limits in order to avoid problems such as anachronism and lack of synchronization. This paper deals with the delay-bounded cost-optimal multicast tree (DBCMT) generation problem. A closely related problem is to find a delay-bounded cost-optimal path (DBCP) between a specified source and destination node. Such a path can be used be used as a starting point to solve the DBCMT. We present here two heuristics for building delay constrained multicast trees which have near optimal cost. A comparison of our heuristics with other proposed heuristics is also presented.
  • No Thumbnail Available
    Item
    Orthogonal moment operators for subpixel edge detection
    (Elsevier, 1993-02) Ghosal, Sugata
    A new approach to detect step edges with subpixel accuracy is presented. The proposed approach is based on a set of orthogonal complex moments of the image known as Zernike moments. An ideal two-dimensional (2D) step edge is modeled in terms of four parameters: the background gray level, the step size, the distance of the edge from the center of the mask, and the orientation of the edge. Discrete Zernike moments are used to obtain a total of three complex masks to compute all the edge parameters for subpixel detection. For pixel-level edge detection only two masks (one real and one complex) are required. The theoretical analysis of the influence of noise on the location and the orientation of an edge is presented. This analysis reveals that the accuracy of the proposed approach is virtually unaffected by the additive noise. The technique is effective in detecting both the pixel-level and subpixel-level edges. Experimental results are presented to demonstrate the efficacy of the proposed technique.
  • No Thumbnail Available
    Item
    Segmentation of range images: an orthogonal moment-based integrated approach
    (IEEE, 1993) Ghosal, Sugata
    A new approach to range image segmentation is presented. The proposed approach involves two phases in which the region and edge information detected using a set of orthogonal Zernike moment-based operators are combined to provide robust segmentation of range images. In the first phase, each range image point is characterized by the surface normal vector and the depth value at that point. A surface feature-based clustering of range image points yields its initial region-based segmentation. This initial segmentation phase often produces oversegmented images. In the second phase of the proposed technique, the oversegmented image is resegmented by appropriately merging adjacent regions using the edge information to produce final segmentation. One attractive characteristic of the proposed technique is that the same set of three moment-based operators is used to extract both surface and edge features. Thus only three convolution operations are needed at an image point to compute all the desired surface and edge features associated with that point. The performances of the proposed Zernike moment-based operators in surface and edge feature detection are theoretically analyzed
  • No Thumbnail Available
    Item
    Detection of composite edges
    (IEEE, 1994-01) Ghosal, Sugata
    The paper presents a new parametric model-based approach to high-precision composite edge detection using orthogonal Zernike moment-based operators. It deals with two types of composite edges: (a) generalized step and (b) pulse/staircase edges. A 2-D generalized step edge is modeled in terms of five parameters: two gradients on two sides of the edge, the distance from the center of the candidate pixel, the orientation of the edge and the step size at the location of the edge. A 2-D pulse/staircase edge is modeled in terms of two steps located at two positions within the mask, and the edge orientation. A pulse edge is formed if the steps are of opposite polarities whereas a staircase edge results from two steps having the same polarity. Two complex and two real Zernike moment-based masks are designed to determine parameters of both the 2-D edge models. For a given edge model, estimated parameter values at a point are used to detect the presence or absence of that type of edge. Extensive noise analysis is performed to demonstrate the robustness of the proposed operators. Experimental results with intensity and range images are included to demonstrate the efficacy of the proposed edge detection technique as well as to compare its performance with the geometric moment-based step edge detection technique and Canny's (1986) edge detector
  • No Thumbnail Available
    Item
    Range surface characterization and segmentation using neural networks
    (Elsevier, 1995) Ghosal, Sugata
    This paper presents an integrated neural net-based approach to the segmentation of range images into distinct surfaces, which is an essential step in range image analysis and interpretation. A two-stage connectionist neural net model is proposed which extracts local surface features at each image point and groups pixels via local interactions among different features. The first stage computes surface parameters, e.g., surface normals, curvature and discontinuities (crease and jump) by optimally projecting the local range profile onto a set of non-orthogonal basis functions. In the second stage, adjacent pixels compete with each other based on the surface features associated with them to group themselves into different surface patches. Daugman's projection neural net (DPNN) and Kohonen's self-organizing neural net (KSNN) are used for the feature extraction and region-growing, respectively. Empirical performance analysis shows that the feature extraction using neural net is quite robust with respect to the additive noise. Experimental results are included to demonstrate the performance of the proposed technique.
  • No Thumbnail Available
    Item
    Target detection in foveal ATR systems
    (IEEE, 1996) Ghosal, Sugata
    Automatic target recognition (ATR) applications require simultaneously a wide field of view (FOV) for better detection and situation awareness, high resolution for target recognition and threat assessment, and high frame rate for detecting brief events and disambiguating frame-to-frame correlation. Uniformly sampling the entire FOV at recognition resolution is simply wasteful in ATR scenarios with localized regions of interest (ROIs). Foveal data acquisition with space-variant sampling and context-sensitive sensor articulation is highly optimized for active ATR applications. We propose a multiscale local Zernike filter-based front end target detection technique for a commercially feasible foveal sensor topology with piecewise constant resolution profile. Anisotropic heat diffusion is employed for preprocessing of the foveal data. Expansion template matching is used to derive a detection filter that optimizes the discriminant signal-to-noise ratio (SNR). Results are presented with simulated foveal imagery, derived from real uniform acuity FLIR data.
  • No Thumbnail Available
    Item
    A fast scalable algorithm for discontinuous optical flow estimation
    (IEEE, 1996-02) Ghosal, Sugata
    Multiple moving objects, partially occluded objects, or even a single object moving against the background gives rise to discontinuities in the optical flow field in corresponding image sequences. While uniform global regularization based moderately fast techniques cannot provide accurate estimates of the discontinuous flow field, statistical optimization based accurate techniques suffer from excessive solution time. A 'weighted anisotropic' smoothness based numerically robust algorithm is proposed that can generate discontinuous optical flow field with high speed and linear computational complexity. Weighted sum of the first-order spatial derivatives of the flow field is used for regularization. Less regularization is performed where strong gradient information is available. The flow field at any point is interpolated more from those at neighboring points along the weaker intensity gradient component. Such intensity gradient weighted regularization leads to Euler-Lagrange equations with strong anisotropies coupled with discontinuities in their coefficients. A robust multilevel iterative technique, that recursively generates coarse-level problems based on intensity gradient weighted smoothing weights, is employed to estimate discontinuous optical flow field. Experimental results are presented to demonstrate the efficacy of the proposed technique.
  • No Thumbnail Available
    Item
    A moment-based unified approach to image feature detection
    (IEEE, 1997-06) Ghosal, Sugata
    In this paper, a novel model-based approach is proposed for generating a set of image feature maps (or primal sketches). For each type of feature, a piecewise smooth parametric model is developed to characterize the local intensity function in an image. Projections of the intensity profile onto a set of orthogonal Zernike-moment-generating polynomials are used to estimate model-parameters and, in turn, generate the desired feature map. A small set of moment-based detectors is identified that can extract various kinds of primal sketches from intensity as well as range images. One main advantage of using parametric model-based techniques is that it is possible to extract complete information (i.e., model parameters) about the underlying image feature, which is desirable in many high-level vision tasks. Experimental results are included to demonstrate the effectiveness of proposed feature detectors.
  • No Thumbnail Available
    Item
    Forced axisymmetric response of linearly tapered circular plates
    (Elsevier, 1994-05) Goyal, Navneet
    Forced axisymmetric response of a circular plate of linearly varying thickness, based on the classical theory, is analyzed by the eigen-function method. An exact solution for the free vibration mode shapes is obtained by the Frobenius method. Clamped and simply-supported plates subjected to symmetric uniformly distributed and concentrated impulsive ring and point loads are solved as example problems. Numerical results computed for transverse deflection and radial stress are plotted in the figures.