Real Time Texture Analysis from the Parallel Computation of Fractal Dimension
Date of Award
Master of Science (MS)
James L. Sehwing
C. Michael Overstreet
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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Hayes, Halford I..
"Real Time Texture Analysis from the Parallel Computation of Fractal Dimension"
(1993). Master of Science (MS), Thesis, Computer Science, Old Dominion University, DOI: 10.25777/gkm8-3v43