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Parallel architectures for image analysis
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Francis, Nicholas David (1991) Parallel architectures for image analysis. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b1410446~S1
Abstract
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.
| Item Type: | Thesis (PhD) | ||||
|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
| Library of Congress Subject Headings (LCSH): | Image processing, Pattern recognition systems, Image analysis, Pattern perception, Computer software, Computer architecture, Computer programming | ||||
| Official Date: | September 1991 | ||||
| Dates: |
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| Institution: | University of Warwick | ||||
| Theses Department: | Department of Computer Science | ||||
| Thesis Type: | PhD | ||||
| Publication Status: | Unpublished | ||||
| Supervisor(s)/Advisor: | Nudd, G. R. | ||||
| Extent: | x, 251 leaves | ||||
| Language: | eng |
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