Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Information-theory-based snake adapted to inhomogeneous intensity variations

Not Accessible

Your library or personal account may give you access

Abstract

A new snake-based segmentation technique of a single object (simply connected) in the presence of inhomogeneous Gaussian noise is proposed, in which the mean in each region is modeled as a polynomial function of the coordinates and which is thus adapted to inhomogeneous illumination. It is shown that the minimization of the stochastic complexity of the image, which can be implemented efficiently, allows one to automatically estimate not only the number and the position of the nodes of the polygonal contour used to describe the object but also the degree of the polynomials that model the variations of the mean.

© 2007 Optical Society of America

Full Article  |  PDF Article
More Like This
Information-theory-based snake adapted to multiregion objects with different noise models

Frédéric Galland and Philippe Réfrégier
Opt. Lett. 29(14) 1611-1613 (2004)

Minimal stochastic complexity snake-based technique adapted to an unknown noise model

Frédéric Galland and Philippe Réfrégier
Opt. Lett. 30(17) 2239-2241 (2005)

Minimal-complexity segmentation with a polygonal snake adapted to different optical noise models

Olivier Ruch and Philippe Réfrégier
Opt. Lett. 26(13) 977-979 (2001)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (3)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (7)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved