Image Understanding Algorithms on Fine-Grained Tree-Structured SIMD Machines

An Important goal for researchers In computer vision is the construction vision systems that Interpret Image data in real time. Such systems typically require a large amount of computation for processing raw Image data at the lowest level, and for sophisticated decision making at the highest level Recent advances In VLSI circuitry· have led to several proposals for parallel architectures for computer vision systems. In this theSIS. we demonstrate that fine-grained tree-structured SIMD machines, which have favorable characteristics for efficient VLSI Implementation, can be used for the rapid execution of a wide range of Image understanding tasks We also Identify the limitations of these architectures and propose methods to ameliorate these difficulties. The NON-VON supercomputer, currently being constructed at Columbia University, is an example of such an architecture. The major contribution of this thesis IS the development and analysis of several parallel Image understanding algorithms for the class of architectures under consideration The algorithms developed In this research have been selected to span different levels of computer vision tasks They Include Image correlation, hlstogrammlng, connected component labeling, the computation of geometric properties, set operations, the Hough transform method for detecting object boundaries, and the correspondence problem In moving light display applications. The algorithms Incorporate novel approaches to reduce the effects of communication bottleneck usually associated With tree architecture

The Connected Component Algorithm on The NON-VON Supercomputer

The NON-VON Supercomputer is a highly parallel tree-structured computer that is being Implemented at Columbia University. In this paper, we demonstrate that tree architectures with their favorable characteristics for VLSI Implementation, and fast global broadcast, lend themselves easily and naturally to the representation and manipulation of Images represented by hierarchical data structures A description of NON-VON architecture IS presented With an emphasis on the special architectural features that will be used m our Image understanding algorithms. We adopt a variation of the quad tree data structure, called the binary Image tree, to represent images in the NON-VON tree We show how Images are loaded in the NON-VON tree, and present the algorithm for budding the binary Image trees. An efficient Implementation of the connected component labeling algorithm on NON-VON is then presented Simulation results are discussed, and we show the fast execution time of the algorithm on NON-VON. Other algorithms are also developed, such as hlstogrammlng, Hough transform, Set operations and Image correlation, and we can conclude that NON-VON can be used to Implement efficiently several :important Image understanding task

Effective Management of Human Resource in Schools of the Future: the Superleadership Paradigm

The impact of technology on education has generated varying possibilities of approaches and techniques in the teaching-learning process in the Malaysian educational setting. In effect, the impact has been pervasive in the management and administrative culture in schools to the extent that there is a growing demand toward a continual building of competency, capacity and capability of educational leaders and managers through various training program

Matrix Elements of Random Operators and Discrete Symmetry Breaking in Nuclei

It is shown that several effects are responsible for deviations of the intensity distributions from the Porter-Thomas law. Among these are genuine symmetry breaking, such as isospin; the nature of the transition operator; truncation of the Hilbert space in shell model calculations and missing transitionsComment: 8 pages, 3 figure

Failure Investigation of a Fill Slope in Putrajaya, Malaysia

On 6th of January 2001, a fill slope collapsed in Putrajaya, Malaysia. The failed slope was 25m in height. The failure caused the slope to pushed two reinforced earth walls and the recently completed jetty and boat docking facilities to collapse. The depth of the failure scar was about 2m with a failure length of about 50m. A failure investigation was then carried out to determine the causes of failure. A total of thirteen new boreholes, fifteen Mackintosh probes and three hand augers were carried out to determine the soil profile. A desk study of existing information and records, site reconnaissance and mapping of the failure area was also carried out to determine the causes and the extent of the failure. Some of the findings of the failure investigation are there were no pile slab found at reinforced earth wall W2 as stated in the drawings and the groundwater table has risen as a result of the filling of the lake, which was carried out after the construction of the fill slope. The groundwater table at failure was found to be much higher than those measured during the site investigation works. Seepages of water were also seen from the failed area