Supporting divide-and-conquer algorithms for image processing

Divide-and-conquer is an important algorithm strategy, but it is not widely used in image processing. For higher-level, symbolic operations it should often be the strategy of choice for parallel computers. It is natural for a machine with a regular interconnection scheme such as a mesh, mesh with broadcasting, tree, pyramid, mesh-of-trees, PRAM, or hypercube, and can be used either on a machine with a pixel per processor or on one with many pixels per processor. However, divide-and-conquer algorithms use parallel computers in a different manner than, say, local edge detection, so machines optimized for local neighborhood algorithms may be poor for divide-and-conquer algorithms. Some characteristics of divide-and-conquer algorithms are examined, along with some of their implications for the design of machines and languages which can support the efficient programming and execution of divide-and-conquer algorithms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26821/1/0000380.pd

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture

Performance analysis of pyramid mapping algorithms for the hypercube

Comparative performance analysis of algorithms that map pyramids and multilevel structures onto the hypercube are presented. The pyramid structure is appropriate for low-level and intermediate-level computer vision algorithms. It is not only efficient for the support of both local and global operations but also capable of supporting the implementation of multilevel solvers. Nevertheless, pyramids lack the capability of efficient implementation of the majority of scientific algorithms and their cost may become unacceptably high. On a different horizon, hypercube machines have widely been used in the field of parallel computing due to their small diameter, high degree of fault tolerance, and rich interconnection that permits fast communication at a reasonable cost. As a result, hypercube machines can efficiently emulate pyramids. Therefore, the characteristics which make hypercube machines useful scientific processors also make them efficient image processors. Two algorithms which have been developed for the efficient mapping of the pyramid onto the hypercube are discussed in this thesis. The algorithm proposed by Stout [4] requires a hypercube with a number of processing elements (PEs) which is equal to the number of nodes in the base of the pyramid. This algorithm can activate only one level of the pyramid at a time. In contrast, the algorithm proposed by Patel and Ziavras [7] requires the same number of PEs as Stout\u27s algorithm but allows the concurren simulation of multiple levels, as long as the base level is not involved in the set of pyramid levels that need to be simulated at the same time. This low-cost algorithm yields higher performance through high utilization of PEs. However it performs slightly worse than Stout\u27s algorithm when only one level is active at a time. Patel and Ziavras\u27 algorithm performs much better than Stout\u27s algorithm when all levels, excluding the leaf level, are active concurrently. The comparative analysis of these two algorithms is based on the incorporation of simulation results for some image processing algorithms which are perimeter counting, image convolution, and segmentation

Implementation of a real time Hough transform using FPGA technology

This thesis is concerned with the modelling, design and implementation of efficient architectures for performing the Hough Transform (HT) on mega-pixel resolution real-time images using Field Programmable Gate Array (FPGA) technology. Although the HT has been around for many years and a number of algorithms have been developed it still remains a significant bottleneck in many image processing applications. Even though, the basic idea of the HT is to locate curves in an image that can be parameterized: e.g. straight lines, polynomials or circles, in a suitable parameter space, the research presented in this thesis will focus only on location of straight lines on binary images. The HT algorithm uses an accumulator array (accumulator bins) to detect the existence of a straight line on an image. As the image needs to be binarized, a novel generic synchronization circuit for windowing operations was designed to perform edge detection. An edge detection method of special interest, the canny method, is used and the design and implementation of it in hardware is achieved in this thesis. As each image pixel can be implemented independently, parallel processing can be performed. However, the main disadvantage of the HT is the large storage and computational requirements. This thesis presents new and state-of-the-art hardware implementations for the minimization of the computational cost, using the Hybrid-Logarithmic Number System (Hybrid-LNS) for calculating the HT for fixed bit-width architectures. It is shown that using the Hybrid-LNS the computational cost is minimized, while the precision of the HT algorithm is maintained. Advances in FPGA technology now make it possible to implement functions as the HT in reconfigurable fabrics. Methods for storing large arrays on FPGA’s are presented, where data from a 1024 x 1024 pixel camera at a rate of up to 25 frames per second are processed

Computing convexity properties of images on a pyramid computer

We present efficient parallel algorithms for using a pyramid computer to determine convexity properties of digitized black/white pictures and labeled figures. Algorithms are presented for deciding convexity, identifying extreme points of convex hulls, and using extreme points in a variety of fashions. For a pyramid computer with a base of n simple processing elements arranged in an n 1/2 × n 1/2 square, the running times of the algorithms range from Θ(log n ) to find the extreme points of a convex figure in a digitized picture, to Θ( n 1/6 ) to find the diameter of a labeled figure, Θ( n 1/4 log n ) to find the extreme points of every figure in a digitized picture, to Θ( n 1/2 ) to find the extreme points of every labeled set of processing elements. Our results show that the pyramid computer can be used to obtain efficient solutions to nontrivial problems in image analysis. We also show the sensitivity of efficient pyramid-computer algorithms to the rate at which essential data can be compressed. Finally, we show that a wide variety of techniques are needed to make full and efficient use of the pyramid architecture.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41351/1/453_2005_Article_BF01759066.pd

Research in progress and other activities of the Institute for Computer Applications in Science and Engineering

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics and computer science during the period April 1, 1993 through September 30, 1993. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustic and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science

Molecular-dynamics simulations of self-assembled monolayers (SAM) on parallel computers

The purpose of this dissertation is to investigate the properties of self-assembled monolayers, particularly alkanethiols and Poly (ethylene glycol) terminated alkanethiols. These simulations are based on realistic interatomic potentials and require scalable and portable multiresolution algorithms implemented on parallel computers. Large-scale molecular dynamics simulations of self-assembled alkanethiol monolayer systems have been carried out using an all-atom model involving a million atoms to investigate their structural properties as a function of temperature, lattice spacing and molecular chain-length. Results show that the alkanethiol chains tilt from the surface normal by a collective angle of 25o along next-nearest neighbor direction at 300K. At 350K the system transforms to a disordered phase characterized by small tilt angle, flexible tilt direction, and random distribution of backbone planes. With increasing lattice spacing, a, the tilt angle increases rapidly from a nearly zero value at a = 4.7Å to as high as 34 o at a = 5.3Å at 300K. We also studied the effect of end groups on the tilt structure of SAM films. We characterized the system with respect to temperature, the alkane chain length, lattice spacing, and the length of the end group. We found that the gauche defects were predominant only in the tails, and the gauche defects increased with the temperature and number of EG units. Effect of electric field on the structure of poly (ethylene glycol) (PEG) terminated alkanethiol self assembled monolayer (SAM) on gold has been studied using parallel molecular dynamics method. An applied electric field triggers a conformational transition from all-trans to a mostly gauche conformation. The polarity of the electric field has a significant effect on the surface structure of PEG leading to a profound effect on the hydrophilicity of the surface. The electric field applied anti-parallel to the surface normal causes a reversible transition to an ordered state in which the oxygen atoms are exposed. On the other hand, an electric field applied in a direction parallel to the surface normal introduces considerable disorder in the system and the oxygen atoms are buried inside

Parallel architectures for image analysis

This thesis is concerned with the problem of designing an architecture specifically for the application of image analysis and object recognition. Image analysis is a complex subject area that remains only partially defined and only partially solved. This makes the task of designing an architecture aimed at efficiently implementing image analysis and recognition algorithms a difficult one. Within this work a massively parallel heterogeneous architecture, the Warwick Pyramid Machine is described. This architecture consists of SIMD, MIMD and MSIMD modes of parallelism each directed at a different part of the problem. The performance of this architecture is analysed with respect to many tasks drawn from very different areas of the image analysis problem. These tasks include an efficient straight line extraction algorithm and a robust and novel geometric model based recognition system. The straight line extraction method is based on the local extraction of line segments using a Hough style algorithm followed by careful global matching and merging. The recognition system avoids quantising the pose space, hence overcoming many of the problems inherent with this class of methods and includes an analytical verification stage. Results and detailed implementations of both of these tasks are given

Proceedings. 25. Workshop Computational Intelligence, Dortmund, 26. - 27. November 2015

Dieser Tagungsband enthält die Beiträge des 25. Workshops „Computational Intelligence“ des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) , der vom 26. – 27. November 2015 in Dortmund stattfindet

High-fidelity rendering on shared computational resources

The generation of high-fidelity imagery is a computationally expensive process and parallel computing has been traditionally employed to alleviate this cost. However, traditional parallel rendering has been restricted to expensive shared memory or dedicated distributed processors. In contrast, parallel computing on shared resources such as a computational or a desktop grid, offers a low cost alternative. But, the prevalent rendering systems are currently incapable of seamlessly handling such shared resources as they suffer from high latencies, restricted bandwidth and volatility. A conventional approach of rescheduling failed jobs in a volatile environment inhibits performance by using redundant computations. Instead, clever task subdivision along with image reconstruction techniques provides an unrestrictive fault-tolerance mechanism, which is highly suitable for high-fidelity rendering. This thesis presents novel fault-tolerant parallel rendering algorithms for effectively tapping the enormous inexpensive computational power provided by shared resources. A first of its kind system for fully dynamic high-fidelity interactive rendering on idle resources is presented which is key for providing an immediate feedback to the changes made by a user. The system achieves interactivity by monitoring and adapting computations according to run-time variations in the computational power and employs a spatio-temporal image reconstruction technique for enhancing the visual fidelity. Furthermore, algorithms described for time-constrained offline rendering of still images and animation sequences, make it possible to deliver the results in a user-defined limit. These novel methods enable the employment of variable resources in deadline-driven environments