The Hough Transform's Implicit Bayesian Foundation
This paper shows that the basic Hough transform is implicitly a Bayesian process-that it computes an unnormalized posterior distribution over the parameters of a single shape given feature points. The proof motivates a purely Bayesian approach to the problem of finding parameterized shapes in digita...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | This paper shows that the basic Hough transform is implicitly a Bayesian process-that it computes an unnormalized posterior distribution over the parameters of a single shape given feature points. The proof motivates a purely Bayesian approach to the problem of finding parameterized shapes in digital images. A proof-of-concept implementation that finds multiple shapes of four parameters is presented. Extensions to the basic model that are made more obvious by the presented reformulation are discussed. |
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ISSN: | 1522-4880 2381-8549 |
DOI: | 10.1109/ICIP.2007.4380033 |