Boundary detection through dynamic polygons |
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Authors: | A Pievatolo & P J Green |
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Institution: | Consiglio Nazionale delle Ricerche, Milan, Italy,;University of Bristol, UK |
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Abstract: | A method for the Bayesian restoration of noisy binary images portraying an object with constant grey level on a background is presented. The restoration, performed by fitting a polygon with any number of sides to the object's outline, is driven by a new probabilistic model for the generation of polygons in a compact subset of R2 , which is used as a prior distribution for the polygon. Some measurability issues raised by the correct specification of the model are addressed. The simulation from the prior and the calculation of the a posteriori mean of grey levels are carried out through reversible jump Markov chain Monte Carlo computation, whose implementation and convergence properties are also discussed. One example of restoration of a synthetic image is presented and compared with existing pixel-based methods. |
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Keywords: | Bayesian object restoration Probability distribution of polygons Reversible jump Markov chain Monte Carlo computation |
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