You are here: Home
/ Publication Information
Title: Active contours on statistical manifolds and texture segmentaiton
Author: Lee, Sang-Mook; Abbott, A. Lynn; Clark, Neil A.; Araman, Philip A.;
Source: IEEE: 828-831
Publication Series: Miscellaneous Publication
Description: A new approach to active contours on statistical manifolds is presented. The statistical manifolds are 2- dimensional Riemannian manifolds that are statistically defined by maps that transform a parameter domain onto-a set of probability density functions. In this novel framework, color or texture features are measured at each Image point and their statistical characteristics are estimated. This is different from statistical representation of bounded regions. A modified Kullback-Leibler divergence, that measures dissimilarity between two density distributions, is added to the statistical manifolds so that a geometric interpretation of the manifolds becomes possible. With this framework, we can formulate a metric tensor on the statistical manifolds. Then, a geodesic active contour is evolved with the aid of the metric tensor. We show that the statistical manifold framework provides more robust and accurate texture segmentation results.
Keywords: statistical manifolds, active contours, texture segmentation, Kullback-Leibler divergence
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
- You may send email to email@example.com to request a hard copy of this publication. (Please specify exactly
which publication you are requesting and your mailing address.)
XML: View XML
Lee, Sang-Mook; Abbott, A. Lynn; Clark, Neil A.; Araman, Philip A. 2005. Active contours on statistical manifolds and texture segmentaiton. IEEE: 828-831
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility