Non-Bayesian Image Feature Detectors

Ivan Kadar, Erica J. Liebman, George Eichmann · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1987

In this paper non-Bayesian and heuristic approaches are applied to the well known problem of image segmentation. The two subproblems in segmentation that were considered were region merge and line detection. For the region merge problem, a comparison was made between the classical Bayes and fuzzy set based approach. Simulations, using a "block world" type real image, were implemented in ZETALISP on the Symbolics 3675 computer. They contrasted the proposed region merge method with the classical implementations. The performance measures of the classical line detection problem, using the Hough transform, are reinterpreted in a non-traditional framework using fuzzy sets and heuristics. Several alternative real-time optical Hough transform schemes are presented as well.

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