NDLI: Exploiting Information Geometry to Improve the Convergence Properties of Variational Active Contours

Content Provider	IEEE Xplore Digital Library
Author	Pereyra, M. Batatia, H. McLaughlin, S.
Copyright Year	2007
Abstract	In this paper we seek to exploit information geometry in order to define the Riemannian structure of the statistical manifold associated with the Chan-Vese active contour model. This Riemannian structure is obtained through a relationship between the contour's Mumford-Shah energy functional and the likelihood of the categorical latent variables of a Gaussian mixture model. Accordingly the natural metric of the statistical manifold formed by the contours is determined by their Fisher information matrix. Mathematical developments show that this matrix has a closed-form analytic expression and is diagonal. Based on this, we subsequently develop a natural gradient algorithm for the Chan-Vese active contour, with application to image segmentation. Because the proposed method performs optimization on the parameters natural manifold it attains dramatically faster convergence rates than the Euclidean gradient descent algorithm commonly used in the literature. Experiments performed on standard test images from the active contour literature are presented and confirm that the proposed natural gradient algorithm delivers accurate segmentation results in few iterations. Comparisons with methods from the state of the art show that the proposed method converges extremely fast, and could improve significantly the speed of many existing image segmentation methods based on the Chan-Vese active contour as well as enable its application to new problems. A MATLAB implementation of the proposed method is available at http://www.stats.bris.ac.uk/~p12320/code/SmoothNaturalGradient4ChanVese.rar.
Sponsorship	IEEE Signal Processing Society
Starting Page	700
Ending Page	707
Page Count	8
File Size	1786856
File Format	PDF
ISSN	19324553
Volume Number	7
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Newton method Active contours Smoothing methods Convergence Manifolds Level set Information geometry variational methods on Riemannian manifolds information geometry level sets
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Exploiting Information Geometry to Improve the Convergence of Nonparametric Active Contours

Exploiting information geometry to improve the convergence of nonparametric active contours

Newton Algorithms for Riemannian Distance Related Problems on Connected Locally Symmetric Manifolds

A Smoothing Active-Set Newton Method for Constrained Optimization

Detection of Local Boundary Using a Variational Level Set Method With Application to Medical Image

Generalized Newton methods for energy formulations in image procesing

Shape-Based Active Contours for Fast Video Segmentation

Harmonic active contours for multichannel image segmentation

Dynamic active contours for visual tracking

Exploiting Information Geometry to Improve the Convergence Properties of Variational Active Contours

Similar Documents

Exploiting Information Geometry to Improve the Convergence of Nonparametric Active Contours

Exploiting information geometry to improve the convergence of nonparametric active contours

Newton Algorithms for Riemannian Distance Related Problems on Connected Locally Symmetric Manifolds

A Smoothing Active-Set Newton Method for Constrained Optimization

Detection of Local Boundary Using a Variational Level Set Method With Application to Medical Image

Generalized Newton methods for energy formulations in image procesing

Shape-Based Active Contours for Fast Video Segmentation

Harmonic active contours for multichannel image segmentation

Dynamic active contours for visual tracking

Exploiting Information Geometry to Improve the Convergence Properties of Variational Active Contours