A graph theoretic approach to transputer network design for computer vision

The work in this thesis is concerned with parallel architectures based on the Inmos transputer-type processors and parallelisation of some computer vision tasks chosen from low to high level. The transputer is a microprocessor with a micro-programmed scheduler and four serial communication links. It directly supports parallel processing since several transputers can be connected through their links to co-operate on solving a problem. Also several processes can be run on the same transputer. A major issue in parallel processing is the communication overhead introduced by parallelising a given task. This overhead is not present in sequential processing and must be curbed if the implementation of a task on a parallel machine is to be successful. The interconnection network underlying the architecture of a parallel computer is therefore of the utmost importance. Computer Vision consists of a hierarchy of tasks ranging from low-level operations dealing with large amounts of relatively simple data to high level operations handling increasingly complex structures. In this work a novel edge detector based on adaptive filtering and an edge detector operating on colour images are presented and implemented on a number of transputers. These parallel implementations together with implementations of vector quantisation, Fourier descriptors for shape discrimination, the Hough transform and the Maximum clique algorithm, offer a notable performance increase when compared with sequential implementations. However, every algorithm required the design of a specific network of transputers to take advantage of the parallelism and data dependencies inherent in each. Consequently, attention is focused on the topology of interconnection networks. In particular, the communication requirements of computer vision algorithms as identified by the various computer vision tasks are analysed. These requirements together with graph theoretical considerations are then used to suggest a topology for large transputer networks. The latter is based on sub-graphs, with proven performance when used to implement interconnection networks, combined to form an architecture with improved performance. This architecture consists of a fixed structure supplemented with a dynamically reconfigured network. After describing this topology, a routing algorithm that conveys messages along shortest paths in the network is given and implemented. And finally, some practical issues in the use of transputers are considered and solutions proposed

Traceable measurement and imaging of the complex permittivity of a multiphase mineral specimen at micron scales using a microwave microscope

This paper describes traceable measurements of the dielectric permittivity and loss tangent of a multiphase material (particulate rock set in epoxy) at micron scales using a resonant Near-Field Scanning Microwave Microscope (NSMM) at 1.2 GHz. Calibration and extraction of the permittivity and loss tangent is via an image charge analysis which has been modified by the use of the complex frequency to make it applicable for high loss materials. The results presented are obtained using a spherical probe tip, 0.1 mm in diameter, and also a conical probe tip with a rounded end 0.01 mm in diameter, which allows imaging with higher resolution (≈10 µm). The microscope is calibrated using approach-curve data over a restricted range of gaps (typically between 1% and 10% of tip diameter) as this is found to give the best measurement accuracy. For both tips the uncertainty of scanned measurements of permittivity is estimated to be±10% (at coverage factor k=2) for permittivity ⪝10. Loss tangent can be resolved to approximately 0.001. Subject to this limit, the uncertainty of loss tangent measurements is estimated to be±20% (at k=2). The reported measurements inform studies of how microwave energy interacts with multiphase materials containing microwave absorbent phases

Full-wave modeling of broadband near field scanning microwave microscopy

The authors would like to thank professor Dr. Gabriel Gomila from Institut de Bioenginyeria de Catalunya (IBEC) and Universitat de Barcelona for the fruitful discussion and support, as well as to Dr. Georg Gramse from Johannes Kepler University Linz for the experimental data. B.W. thanks the funding from the China Scholarship Council (CSC) for the support of his research at Queen Mary University of London, UK. Y.H. would like to thank EU-FP7 Nanomicrowave project for the financial support