Date of Award

Summer 7-1993

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Committee Director

James L. Sehwing

Committee Member

C. Michael Overstreet

Committee Member

Stephen Olariu

Call Number for Print

Special Collections LD4331.C65H39

Abstract

The discrimination of texture features in an image has many important applications: from detection of man-made objects from a surrounding natural background to identification of cancerous from healthy tissue in X-ray imagery. The fractal structure in an image has been used with success to identify these features but requires unacceptable processing time if executed sequentially.

The paradigm of data parallelism is presented as the best method for applying massively parallel processing to the computation of fractal dimension of an image. With this methodology, and sufficient numbers of processors, this computation can reach real time speeds necessary for many applications. A model is analyzed and evaluated on several architectures: workstation, vectorizing supercomputer, shared-memory MIMD, and massively parallel SIMD computers. Per expectations, results in the subsecond range are attained on the massively parallel SIMD computer.

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In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

DOI

10.25777/gkm8-3v43

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