Date of Award

Summer 7-1993

Document Type


Degree Name

Master of Science (MS)


Computer Science

Committee Director

James L. Sehwing

Committee Member

C. Michael Overstreet

Committee Member

Stephen Olariu

Call Number for Print

Special Collections LD4331.C65H39


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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