Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
530820 | Pattern Recognition | 2008 | 9 Pages |
Abstract
We give the analytical definitions of the Chernoff, Bhattacharyya and Jeffreys–Matusita probabilistic distances between two Dirichlet distributions and two Beta distributions as its special case. For all other known probabilistic distances we show their inappropriateness in the analytical case. We discuss the parameter learning of the Dirichlet distribution from a finite sample set and present an application for split-and-merge image segmentation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
T.W. Rauber, T. Braun, K. Berns,