Showing papers by "Kamala Krithivasan published in 2008"

Efficient Algorithms for Reconstruction of 2D-Arrays from Extended Parikh Images

Abstract: The concept of a Parikh matrix or an extended Parikh mapping of words introduced by Mateescu et al (2001) is formulated here for two-dimensional (2D) arrays. A polynomial time algorithm is proposed to reconstruct an unknown 2D-array over { 0,1 } from its image under the extended Parikh mapping along a single direction. On the other hand the problem of reconstructing a 2D-array over { 0,1 } from its image under the extended Parikh mapping along three or more directions is shown to be NP-hard. Also a polynomial time algorithm to reconstruct a 2D-array over {0,1} with a maximum number of ones close to the main diagonal of the array is presented by reducing the problem to Min-cost Max-flow problem.

Graph Splicing Systems.

Abstract: A fountain pen in which ink is supplied to the tip of the pen under the control of a motor-actuated ink delivery device. An ink holder is formed covering the slit formation region of the pen tip to form an ink pool between the holder and pen tip. A detector is provided in the ink pool for detecting the quantity of ink therein at any time. A pen holder coupled to the pen tip includes an ink storing section opening into the ink pool, an ink delivery device coupled to the ink storing section for delivering ink under pressure, and an electrical power source and a power delivery circuit for controlling the flow of current to an operating motor.

Algorithm for Reconstructing 3D-Binary Matrix with Periodicity Constraints from Two Projections

Abstract: We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object(crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject(crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections. Keywords—3D-Binary Matrix Reconstruction, Computed Tomography, Discrete Tomography, Integral Max Flow Problem.

A min-cost-max-flow based algorithm for reconstructing binary image from two projections using similar images

Abstract: The aim of this paper is to study the reconstruction of binary images from two projections using a priori images that are similar to the unknown image. Reconstruction of images from a few projections is preferred to reduce radiation hazards. It is well known that the problem of reconstructing images from a few projections is ill-posed. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. We use a priori images that are similar to the unknown image, to reduce the class of images having the same two projections. The a priori similar images may be obtained in many ways such as by considering images of neighboring slices or images of the same slice, taken in previous time instances. In this paper, we give a polynomial time algorithm to reconstruct binary image from two projections such that the reconstructed image is optimally close to the a priori similar images. We obtain a solution to our problem by reducing our problem to min cost integral max flow problem.