1 December 2001 Stochastic algorithm for approximating soft morphological operators
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Optical Engineering, 40(12), (2001). doi:10.1117/1.1419022
Abstract
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.
Michael A. Zmuda, "Stochastic algorithm for approximating soft morphological operators," Optical Engineering 40(12), (1 December 2001). http://dx.doi.org/10.1117/1.1419022
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KEYWORDS
Image processing

Stochastic processes

Logic

Selenium

Binary data

Image analysis

Optical engineering

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