1 December 2001 Stochastic algorithm for approximating soft morphological operators
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A technique that approximates the output of the soft morphological operators is described. The soft operators can be viewed as a voting process across neighborhoods defined by the structuring element. Instead of processing all votes across a neighborhood, this approximation technique randomly samples elements in the neighborhood and uses these values as inputs to a two-state finite state machine, where the state of the machine corresponds to the output at a given pixel. When properly designed, the machines sample a small fraction of the neighborhood, obtain output that is 91 to 100% accurate at each pixel, and is one to two orders of magnitude faster than conventional algorithms. Experiments on binary textures and digits confirm the theoretical results.
©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)
Michael A. Zmuda "Stochastic algorithm for approximating soft morphological operators," Optical Engineering 40(12), (1 December 2001). https://doi.org/10.1117/1.1419022
Published: 1 December 2001
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Cited by 2 scholarly publications.
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KEYWORDS
Image processing

Stochastic processes

Logic

Selenium

Binary data

Image analysis

Optical engineering

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