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ICPR
2010
IEEE

Statistical Shape Modeling using Morphological Representations

14 years 5 months ago
Statistical Shape Modeling using Morphological Representations
The aim of this paper is to propose tools for statistical analysis of shape families using morphological operators. Given a series of shape families (or shape categories), the approach consists in empirically computing shape statistics (i.e., mean shape and variance of shape) and then to use simple algorithms for random shape generation, for empirical shape confidence boundaries computation and for shape classification using Bayes rules. The main required ingredients for the present methods are well known in image processing, such as watershed on distance functions or log-polar transformation. Performance of classification is presented in a well-known shape database.
S. Velasco-Forero and J. Angulo
Added 10 May 2010
Updated 17 May 2010
Type Conference
Year 2010
Where ICPR
Authors S. Velasco-Forero and J. Angulo
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